Malaria and neurological complications: intersecting mechanisms, disease models, and artificial intelligence-based diagnosis

Abstract

INTRODUCTION: In 2022, approximately 608,000 deaths worldwide were attributed to malaria. Beyond its high mortality rates, malaria is responsible for numerous long-lasting complications in survivors, including neurological deficits. Globally, over 1 billion individuals live with various neurological disorders, leading to seven million deaths annually.

OBJECTIVE: Overcoming challenges associated with disease modeling and developing advanced techniques to investigate the neurological consequences of malaria are of great importance. Examining the influence of imbalanced gut microbiota and shared genetic factors on malaria progression and specific neurological conditions is advancing our understanding of neurodegenerative and neurocognitive impairments in malaria survivors. Some common molecular mechanisms shared by both malaria and neurological pathologies, including disruptions in the blood-brain barrier, neuroinflammation, and increased amyloid-β (Aβ) levels, have been studied. This review explores the pathogenesis of Plasmodium infection, highlighting molecular events in the intersecting mechanisms of malaria and Alzheimer’s disease (AD). The application of artificial intelligence and machine learning-based diagnostic tools is also of interest in this area, as they offer promising solutions for diagnosis and treatment.

CONCLUSION: By elucidating the intersecting mechanisms of malaria and AD, this paper provides valuable insights into early detection methods and potential treatment strategies that may enable effective management of neurodegenerative progression in individuals affected by malaria.

Main article text

INTRODUCTION

Malaria is a life-threatening disease transmitted to humans by female Anopheles mosquitoes, primarily in tropical countries. Five Plasmodium parasite species cause malaria in humans, with P. falciparum and P. vivax posing the greatest threat. P. falciparum is the deadliest malaria parasite and is most prevalent on the African continent. P. vivax is the dominant malaria parasite in most countries outside of sub-Saharan Africa. The other malaria species that can infect humans are P. malariae, P. ovale, and P. knowlesi [1]. Common symptoms of malaria include fatigue, chills, fever, and anemia, although complications can be far more severe, especially for disease caused by P. falciparum. The World Health Organization (WHO) characterizes malaria as a severe infection caused by Plasmodium that leads to organ failures (such as spleen and liver), mortality, and disorders of the nervous system including psychiatric complications [1]. In 2020, approximately 241 million cases of malaria were reported worldwide, including 627,000 deaths. Notably, around 77% of these cases were detected in children under 5 years of age [2]. Malaria caused by P. falciparum is typically observed in tropical and subtropical regions, with most cases and mortality seen in the WHO African Region (AFRO). Four countries in sub-Saharan Africa (Nigeria, Democratic Republic of the Congo, Uganda, and Mozambique) accounted for nearly 50% of all malaria deaths worldwide in 2021 [3].

This disease has severe pathophysiological effects on all body systems of infected individuals, primarily impacting the brain and impairing its functionality [4]. Major risks associated with P. falciparum malaria involve infection of the central nervous system with rapid development of major complications that often result in mortality [4]. Affected individuals generally experience coma; however, the onset of an array of neurological impairments varies from sudden to gradual [5]. Additionally, typical effects of malaria involve blindness, deconjugated stare, ocular deviation, abnormal postures, rigidity, seizures, and electroencephalographic anomalies [6].

In individuals with P. falciparum infection, the parasite modifies the red blood cell membrane, causing cells to be sequestered when passing through the microvasculature, leading to impairment of the blood-brain barrier (BBB) [6]. Severe neurological inflammation results from leukocyte, cytokine, CD8+ T cell, and chemokine extravasation into the cerebral parenchyma [7]. Although cerebral malaria is fully recoverable, 15-20% of patients may die, and >20% of patients may experience long-term conditions such as hemiplegia, aphasia, cortical blindness, and ataxia that represent neurodegenerative complications from malaria. Studies have found a profound impact of these changes on the progression of former cerebral malaria patients towards neurological impairments [8]. This severely impacts the well-being of affected individuals and has profound social consequences [9]. Examples of neurological impairments observed in survivors of severe malaria described by Rosa-Gonçalves et al. [10] are shown in Table 1.

Table 1.

Neurological repercussions seen in the survivors of severe malaria

Type of outcome	Examples of diseases
Neurological impairments	Motor deficits, ataxia, paresis Movement disorders, seizure Visual and hearing impairments
Cognitive deficits	Development delay Attention deficits Learning difficulties Cognitive ability deficits
Behavioral alterations	Emotional reactions and disruptive behaviors Attention deficit and hyperactivity disorders Sleep problems and anxiety

The development of proper disease models that describe the neurological impact of P. falciparum induced sequestration in the brain is necessary to progress in the search for new therapeutics. Similarly, disease models for neurological disorders have been scarce for a long time due to the inability to acquire cells from living individuals [11]. Moreover, considering that malaria affects people in low-income countries with the majority living in remote areas, early detection plays a critical role in protecting against the disruption of BBB [12]. Although malaria is largely treatable, common pathological pathways are leading to neurodegeneration and neurocognitive changes due to delays in diagnosis. Artificial intelligence (AI) and machine learning (ML) algorithms can play an important role in facilitating early detection of the disease [12]. This review covers the neuropathogenesis of P. falciparum infection and related effects on neurodegeneration and cognition. The pathophysiological pathways of the condition and the associated brain-related disruptions are discussed in detail. The novelty of the review lies in discussion of the intersection between malaria infection and the neurophysiological changes leading to the development of neurological impairments. Current diagnostic tools and the possible role of AI in the early detection of malaria have been explored in the context of prevention of severe disease. PubMed, Scopus, and Google Scholar databases were searched for papers published between 2000 and 2024 using the following keywords: cerebral malaria, neurological impairments in cerebral malaria, challenges in cerebral malaria detection, AI in detecting cerebral malaria. The corresponding publications on the mechanisms of cerebral malaria and related neurological impairments are included in this review.

Infection of Plasmodium parasites and progression mechanisms

Life cycle of Plasmodium parasites

The Plasmodium parasite life cycle has a complex pattern that includes infecting a human intermediate host for an asexual phase and an Anopheles mosquito as a definitive host for the sexual phase [13]. The cycle begins when a female mosquito injects transmissive sporozoites into the human body during a blood meal. The sporozoites circulate within the bloodstream or lymphatic system and invade the liver, where they proliferate inside hepatocytes to give rise to liver schizonts that eventually produce thousands of invasive haploid merozoites. These merozoites enter their next target – erythrocytes – after being released into the bloodstream. Inside the erythrocytes, schizogony continues, and the parasite converts from the signet ring stage through trophozoites into the schizont stage [14]. While the parasite is inside red blood cells (RBCs) in the ring stage for approximately 24 h, it is highly immotile. Multiple ring stages can be observed in individuals infected with P. falciparum, serving as a diagnostic marker. Inside erythrocytes, the parasite undergoes asexual reproduction to form merozoites. This leads to erythrocyte rupture and release of merozoites that invade new blood cells. The incubation period in erythrocytes differs among species, with 48 h being the timeframe for P. falciparum [14]. As the parasites multiplying inside erythrocytes convert into gametocytes (macrogametocytes (female) or microgametocytes (male)), the sexual phase of their life cycle begins. During a blood meal from an infected person, both types of gametocytes are ingested by the female mosquito. Male gametocytes produce flagellated microgametes capable of fertilizing a macrogamete, eventually forming a zygote. This stage progresses into a motile ookinete that becomes encysted to form an oocyst. This is followed by sporogony, during which hundreds of motile sporozoites form inside the oocyst. Mature sporozoites burst the oocyst and are released into the hemocoel of the mosquito, ultimately reaching the salivary glands and awaiting transmission to a new human host [14]. Transmission of sporozoites to a new human host perpetuates the malaria life cycle (Fig. 1).

Fig. 1.

Malaria life cycle.

Red blood cell reorganization driven by parasites

Erythrocytic schizogony in P. falciparum infection necessitates substantial rearrangement of the host RBC membrane and cytoplasm to survive against the host’s defense system [15]. This ultimately results in the creation of Maurer’s clefts, the cisternae of which are connected to the infected RBC’s (iRBC) plasma membrane by actin filaments that facilitate the trafficking of vital parasite proteins [16]. P. falciparum erythrocyte membrane protein 1(PfEMP1) is one of these vital compounds necessary for host-parasite interaction; it is transported to the iRBCs’ surface and appears on protrusions on the cell membrane [17, 18]. PfEMP1’s proper transport and presentation facilitates cytoadherence, enabling the iRBC to attach to receptors on various human body cells, including endothelial cells surrounding the post-capillary venules of the brain, kidneys, lungs, and syncytiotrophoblasts in the placenta [15]. P. falciparum-iRBCs preferentially sequester on the endothelium of the smallest vessels (i.e., capillaries and post-capillary venules), leading to localized occlusions and inflammation [19]. Immunohistochemistry on autopsy brain tissues from patients has shown activation of endothelial cells and macrophages, and disruption of endothelial intercellular junctions in vessels containing sequestered parasitized erythrocytes [20].

PfEMP1 binding to the appropriate receptor determines the location of cytoadherence and, by mimicking leukocyte rolling adhesion, effectively keeps the iRBC within the organ’s vascular bed until erythrocytic schizogony is complete and merozoites exit the iRBCs to locate and infect fresh host RBCs. Hypoxia and ischemia are caused by the prolonged presence of iRBCs in inner organs [21]. The primary function of PfEMP1 proteins is to facilitate infected erythrocyte (IE) adherence to host receptors in the vasculature. The adult IEs, which are malformed and rigid due to the parasites developing inside them, can bypass splenic passage (where they would be filtered and destroyed) thanks to this sequestration, which is essential for parasite survival. Numerous vascular surface proteins and carbohydrates, such as CD intercellular adhesion molecule 1 (ICAM-1), endothelial protein C receptor (EPCR), oncofetal chondroitin sulfate (ofCS), and ABO blood group antigens, can function as IE adhesion receptors. Different vascular beds express IE adhesion receptors differently, and cytokines are frequently involved in this regulation [19]. The selectivity of several PfEMP1 proteins for the same receptor is somewhat consistent with the previously reported structurally defined PfEMP1 groups and domain subclasses. ICAM-1 is bound by Duffy-binding-like domain β (DBLβ) domains present in Groups A, B, and C PfEMP1. Groups B and C have CIDRα2-6 domains that bind CD36, while CIDRα1 domains from Group A and B/A PfEMP1 bind EPCR (Fig. 2). Lastly, Group E (VAR2CSA-type) PfEMP1 exhibits a distinct affinity for CSA and appears to be responsible for IE accumulation in the placenta. It is unsurprising that a few of these large, multidomain proteins have domains that can mediate adhesion to multiple host receptors simultaneously [17-18]. The complex containing iRBCs and platelets adheres to the endothelium and is sequestered in the brain of infected individuals, leading to the development of cerebral malaria [15].

Fig. 2.

Disruption of BBB.

Intersecting mechanisms of malaria and neurological impairments

Neurodegenerative disorders involve several structural and functional changes in the brain that are primarily related to impairments in memory and neurological function. Studies have identified several mechanisms that intersect with those of malaria. It is important to understand that malaria can trigger the development of neurological disorders such as Alzheimer’s disease, seizures, motor deficits, attention deficits, and anxiety in survivors. These effects occur through common mechanisms including neuroinflammation, BBB disruption, and oxidative stress. In sub-Saharan Africa, where the incidence of cerebral malaria (CM) is high, an estimated 2.13 million people were living with dementia in 2015. According to the WHO, this number is projected to nearly double every 20 years, rising to 3.48 million by 2030 and 7.62 million by 2050 [22]. The major intersecting mechanisms are discussed below.

Microvascular obstruction and BBB disruption

The BBB is composed of a continuous endothelial membrane covered by mural vascular cells and astrocyte end-feet in the microvessels [23]. The BBB shields brain neurons from external stimuli and ensures precise synaptic and neuronal function [24]. When the BBB is disrupted, toxins and pathogens enter the brain, causing inflammation and immunological reactions that can damage neurons and cause impairments. Pericytes and astrocytes typically guard the junctions of brain microvascular endothelial cells (BMECs) in the brain neurovascular unit [25].

The sequestration of infected RBCs (iRBCs) by BMECs during Plasmodium infection disrupts BBB integrity. The brain endothelium develops vasoconstriction, proinflammatory, and prothrombotic conditions during malaria [24]. As a result, endothelial cells function abnormally, leading to dysfunction [1]. Research indicates that the brain endothelium facilitates iRBC adhesion to cerebral microvessels in cerebral malaria, resulting in vasospasms, altered vasoregulatory components, ischemia, inflammation, and BBB leakage. Consequently, sequestered iRBCs and platelets obstruct the endothelial lining [26, 27]. Vasoconstriction, barrier disruption, and increased neuroinflammation are exacerbated by rigid and clumped iRBCs, platelets, and white blood cells [28]. The rupture of iRBCs causes excretion of hemozoin and parasite toxins like glycosylphosphatidylinositols, which disrupt BBB integrity in combination with host cytokines and chemokines [17].

Studies have found that the cerebral endothelium uses ICAM-1 to sequester iRBCs, causing endothelium enlargement and BBB disruption [29, 30]. The sequestration of iRBCs in the brain microvasculature leads to endothelial dysfunction and leakage, followed by the release of parasitic toxins into the brain parenchyma and immunological repercussions from the host as a burst of cytokines and chemokines, with further BBB leakage (Fig. 2).

Cerebral neuroinflammation

Neuroinflammation plays a crucial role in the development of neural degeneration. Research shows that astrocytes and microglia in CM react to P. falciparum through immune responses. Leukocytes, cytokines, chemokines, iRBCs, and parasite toxins penetrate the parenchyma after BBB disruption [31].

These molecules can activate glial cells, which in turn cause immune cells to release more active mediators like cytokines and chemokines, resulting in increased neuroinflammation [32]. Astrocytes and microglia cells in the extracellular matrix release IL1, IL6, TNFα, endothelin-1, CCL2, and reactive oxygen species, which intensify neuroinflammation [33]. Occasionally, transforming growth factor-beta (TGFβ), matrix metalloproteinases (MMPs), astrocytes, pericytes, and microglia also produce vascular endothelial growth factor A (VEGF-A), exacerbated by BBB disruption [34]. This further worsens neuronal damage and cognitive impairments [26]. Chronic neuroinflammatory conditions lead to neuronal deterioration, which is why malaria can be associated with conditions such as Alzheimer’s disease [35].

Research shows that AD patients exhibit generation of inflammatory chemokines and cytokines surrounding affected neurons in their brains [36]. Recent genome-wide association studies (GWAS) have revealed that a significant number of genes linked to neurodegeneration risk are enriched in microglia and associated with immune responses [37]. Furthermore, a sizable fraction of the identified genes was found to be present in macrophages and microglia [38]. Microglia experience alterations in their gene expression profiles, leading to rapid production of various inflammatory cytokines and transformation into amoeboid morphology [39]. It can be inferred that chronic neuroinflammation, a common feature of malaria, may interfere with microglia’s ability to perform homeostatic functions, leading to neuronal loss. Moreover, neuroinflammation seen in malaria can be linked to neurological conditions like epilepsy [40]. Such episodes can become more prominent in malaria survivors later in life. Evidence shows that increased neuronal excitability — the major characteristic feature of epilepsy — is accompanied by neuroinflammation and initiates and propagates seizures [41]. Fig. 3 represents the role of microglia in neuroinflammation during malaria leading to neurotoxicity. In normal individuals, the protective role of microglia creates neural homeostasis, which breaks down during the release of pro-inflammatory cytokines, leading to neurodegeneration.

Fig. 3.

The role of microglia in neuroinflammation leading to neurotoxicity during malaria.

Enhanced levels of β-amyloid and Tau

Tau is a marker of neuronal axon damage, where it maintains microtubule networks. In neurologic disorders, plasma Tau levels indicate the degree of diffuse axonal injury [9, 42, 43]. AD is characterized by brain accumulation of amyloid-β (Aβ) peptides, an end product of amyloid precursor protein (APP) degradation, which occurs before Tau is hyperphosphorylated to form toxic neurofibrils. Increased Tau concentrations in cerebrospinal fluid (CSF) have been found in cerebral malaria as well as in various neurologic disorders, including AD [4]. Furthermore, apolipoprotein E (APOE), a cholesterol-transporting protein secreted by astrocytes in AD, regulates APP transcription and Aβ clearance [45]. AD patients’ CSF has higher levels of APP and APOE [46, 47]. Research indicates that Aβ amyloidosis is significantly reduced in a gene dose-dependent manner when APOE is absent [48]. Among the three isoforms of APOE (APOE2, APOE3, and APOE4), APOE4 is the main inherited factor responsible for neurodegeneration. An APOE4 variant has been found to cause neurodegeneration by accumulating APP and Aβ. Research has also linked an APOE4 variant to malaria-like vascular dysfunction and BBB leakage, which occur before the onset of AD [45]. However, contradictory research has found that high APOE frequency may offer a selective advantage against P. falciparum. There appears to be evolutionary pressure selecting APOE 4/4 individuals, even showing lower survival in later age [49]. Recent studies from the Chandy John lab have found contradictory results: APOE4 is associated with a higher risk of CM and mortality in children, but better long-term cognition in survivors below 5 years of age [50].

Combining these research findings, it can be concluded that amyloidosis — primarily caused by the co-upregulation of APP and APOE in the brain — is a common process underlying the neurological symptoms of both AD and malaria [51]. To prevent post-infection neurodegeneration in cerebral malaria patients after recovery, therapies targeting amyloidosis may be investigated [8]. However, the cerebral molecular processes that initiate neurological dysfunction in cerebral malaria remain a subject of debate. Hypotheses supported by molecular data have been proposed to link APOE-mediated amyloidosis to neurodegeneration in cerebral malaria [51]. A comparison of Aβ and Tau can be observed in Fig. 4.

Fig. 4.

Comparison of Aβ and Tau in healthy and degenerating brain.

Genetic factors common to malaria and neurodegenerative diseases

Several genetic factors have been found to be common in cerebral malaria and neurodegenerative diseases. Transcriptome analyses of peripheral blood mononuclear cells (PBMCs) from malaria patients have revealed alterations in the expression of genes associated with the human innate immune pathway [54]. Research provides the first evidence of pathogenic mechanisms shared by human malaria and neurodegenerative conditions. SNCA, SIAH2, UBB, HSPA1A, TUBB2A, and PINK1 were among the major causal genes for multiple neurological conditions upregulated (fold-increases ≥2.6) in cerebral sample transcripts, while UBD and PSMC5 were notably downregulated. SNCA, which encodes α-synuclein, a brain-specific protein, has been identified as a major causal gene in distinct neurodegenerative disorders such as Parkinson’s disease [55]. The oxygen deprivation response, commonly seen in malaria patients, is largely dependent on the E3 ubiquitin-conjugating enzyme encoded by SIAH2, one of the overexpressed genes [56]. SIAH2 messenger RNA levels rise in hypoxia, and the protein it encodes interacts toxically with α-synuclein. PTEN-induced kinase 1 (PINK1), a mitochondrial kinase, has been shown to be present at elevated levels in the bloodstreams of affected individuals [57]. The β-tubulin-encoding gene TUBB2A was also overexpressed during malaria and is linked to human brain impairment and infantile-onset epilepsy [58]. HSP-70 levels have been associated with the duration and intensity of seizures in patients with epilepsy, and research found that HSPA1A was elevated in malaria patients as well. Determination of the underlying processes of disease progression could be facilitated since malaria and other neurodegenerative diseases have similar pathogenic mechanisms involving common genes and analogous genetic control system [55].

Dysbiosis: the imbalance of gut microbiome

The gut microbiota (GM) is a group of bacteria, fungi, and protozoa that has colonized gastrointestinal tracts and co-evolved with the host [59]. Significant impact of GM on numerous biological processes, including regulation of host metabolism, local and systemic immune regulation, and neural growth, explain it’s critical role in human health [60, 61]. Research indicates that dysbiosis, or abnormal alterations in GM composition, can cause several abnormalities, including neurological impairments connected to neuroinflammation such as seizures and epilepsy [62].

Studies suggest a connection between dysbiosis and gastrointestinal barrier leakage, which can exacerbate cerebral inflammation by triggering inflammatory reactions and releasing harmful chemicals into the bloodstream [63]. Research has revealed that GM can impact BBB integrity through immune modulation and by influencing bacterial metabolites [64, 65]. These preclinical findings were validated in a study involving P. falciparum-infected individuals residing in a remote Mali village. Initial findings suggested that dysbiosis affected neuroinflammation in C57BL/6 mice with cerebral malaria, caused by infection with P. berghei ANKA, by altering microglia’s pro-inflammatory response [66]. These findings are consistent with published research demonstrating that P. berghei ANKA infection causes alterations in the GM that affect malaria severity [67]. Research indicates that BBB disruption can be linked to increased penetration of IL17, IL22, and bacterial byproducts like butyrates [68]. This increases glutamate levels, which in turn causes neuronal death in the brain [68, 69] (summarized in Fig. 5).

Fig. 5.

The influence of GM on BBB integrity and malaria severity.

Oxidative stress

Through the upregulation of antioxidant enzymes, enhancement of phagocytosis, and oxidative stress induced by antimicrobial medications — all of which can be harmful to P. falciparum parasites — host innate immune cells, including monocytes, macrophages, and neutrophils, play a critical protective role in malaria [1]. An increase in reactive oxygen species (ROS) production aids in parasite removal. Activated epithelial cells (ECs) can produce increased reactive nitrogen species (RNS) and ROS, which in turn can cause proinflammatory cytokines (TNFα, IL1, IL6) and chemokines (MCP1/CCL2, CXCL8/IL8) to be secreted more rapidly within the parenchyma [36]. This may also result in severe neurodegeneration, excessive infection, or hyperinflammation [70]. Each of these components is essential to the development of tissue edema and entry of leukocytes into the brain parenchyma in cerebral malaria [71].

An inflammatory cytokine storm results from the persistent activation of immunocompetent cells by cytokines and chemokines, which also increases ROS production via NADPH oxidase [72]. The ultimate consequence is increased activation and damage to immunocompetent cells, causing axonal damage, neurodegeneration, and neurocognitive deficits [73]. Evidence of oxidative stress in AD has been confirmed through increases in oxidized proteins, enhanced glycation end products, and formation of toxic species like peroxides, alcohols, aldehydes, free carbonyls, ketones, and cholestenone [74]. Moreover, in epileptic patients, oxidative stress leads to the malfunctioning of neurotransmitter proteins, resulting in synaptic impairments [41]. The connection between malaria and the development of epileptic seizures can be readily correlated through these findings.

Disease models: advanced 2D and 3D in vitro models

One of the predominant challenges in studying neurological disorders like cerebral malaria and AD is accessing brain cells and tracking them in real-time through various stages [75]. Brain endothelium research primarily uses conventional techniques such as transwell experiments, parallel artificial membrane permeability assays (PAMPA), brain microvascular endothelial cell (BMVEC) subcultures, and in vivo models. PAMPA’s oversimplification is a major limitation, as it fails to fully capture the complexity and heterogeneity of the specialized BBB endothelium [76]. Due to interspecies differences, animal models of malaria differ significantly from human systems, even though in vivo models are typically considered the most physiologically relevant because the brain endothelium is surrounded by its local microenvironment.

Conventional in vitro 2D modeling provides a more appropriate solution to overcome these translational barriers by using human BBB endothelial cells co-cultured with other glial cells [77]. However, these models lack several specific brain microvascular features, such as lumen characteristics, blood flow, and the resulting shear stress [78].

Organoids and organ-on-chip technology, two recent developments in dynamic 3D disease modeling, can provide more physiologically relevant structures to understand the molecular mechanisms involved in malaria [79]. Brain organoids are sophisticated structures used to investigate organogenesis and the delivery of molecules that penetrate the brain. By maintaining cellular constituents in proximity without artificial membranes, they provide a system that accurately depicts complex cellular interactions [80]. Researchers have even utilized human 3D brain organoids to study heme-mediated brain injury associated with cerebral malaria [81]. Table 2 depicts the models used to investigate neurological effects of malaria with their potential drawbacks.

Table 2.

Disease models typically used for the research on cerebral malaria with their potential drawbacks

Disease Models	Disadvantages	References
2D parallel artificial membrane permeability assays	Unable to capture the complexity of the specialized BBB endothelium	[76]
2D Transwell models	Lack several specific brain microvascular features, such as lumen characteristics, blood flow, and the resulting stress	[78]
3D human brain organoids	Inability to replicate controlled blood flow and lack of ability to represent physiological branching of blood vessels	[81]
3D bioprinted structures	Expensive equipment and poor choice of bionics	[82]
In vivo-models (murine)	Lack of physiological and metabolic similarity with human brain	[83]
Non-human primates	Availability, handling	[84, 85, 86]

The Jensen group has utilized 3D human BBB organoids as a model for Lyme neuroborreliosis, highlighting genospecies-dependent organotropism. Such models can be highly valuable for studying the impact of P. falciparum on the brain [87]. The Bernabeu and Smith group utilized bioengineered human 3D microvessels to investigate P. falciparum pathogenesis [88].

3D olfactory neurosphere-derived cells can serve as a valuable model for cerebral malaria and neurological impairments, representing disease-related variations. Studies employing this model have contributed to the identification of potential genes involved in neurodegeneration, such as A-kinase anchoring protein 6 (AKAP6), which warrant further investigation [11]. RNA sequencing of neurosphere-derived cells of olfactory origin from AD patients has provided valuable insights into the expression patterns of markers associated with neuronal-glial cell differentiation, offering a novel model to investigate alterations in early AD-related pathways [89]. Moreover, olfactory neurospheres can replicate oxidative stress associated with various neurological conditions like Alzheimer’s, Parkinson’s, or epilepsy. Notably, the use of fluorescence lifetime imaging microscopy has significantly aided in detecting oxidative alterations with minimal impact on cellular physiology [90].

Treatments focused on common benefits to malaria and neurological impairments

Current treatment strategies for cerebral malaria include therapies used in conjunction with available antimalarials to halt disease progression and prevent or reverse BBB dysfunction that causes neuroinflammation. A novel formulation of nano-sterically stabilized liposome-encapsulated β-methasone hemisuccinate (BMS) has shown promise for treating experimental cerebral malaria (ECM) using the murine P. berghei ANKA model [91].

Nevertheless, in the majority of cerebral malaria patients, elevated doses of artemisinin derivatives have been found insufficient to prevent brain damage [92]. Consequently, medications commonly used as rapid-acting antimalarials, such as mefloquine, quinine, and chloroquine, can help reduce neurological disorders and/or prevent death in cerebral malaria patients. These drugs act by reducing or eliminating endothelial dysfunction, a crucial step in malaria pathophysiology, via activation of the PI3K/Akt/eNOS pathway [93]. Artemisinin derivatives protect against the neurocognitive consequences of malaria [94]. Corticosteroids (dexamethasone), intravenous immunoglobulin, and peroxisome proliferator-activated receptor γ (PPARγ) agonists have all been utilized as additional treatments in malaria with varying degrees of success [95].

The free radical scavenger edaravone is employed to treat neurodegenerative disorders [96]. Broad-spectrum immunomodulatory drugs such as pentoxifylline, oral-activated charcoal, and PPARγ agonists may help preserve endothelial integrity by inhibiting natural immune responses that could damage the endothelium [97]. These immune modulators support improved neural protection, upregulation of antioxidant systems in malaria, and prevention of inflammation and endothelial dysfunction. Several drugs, including steroids, have undergone clinical trials for malaria [98], but results are not always encouraging, as seen with dexamethasone and pentoxifylline, where adverse effects and even increased mortality were observed [99, 100]. Overall, the use of traditional anti-parasite medications along with vasoprotective therapies that safeguard the BBB and endothelial function may considerably lower death rates, reduce neurological inflammation and damage, and protect against cognitive decline that could result in neurological impairments [101].

Challenges in diagnosis and treatment: role of artificial intelligence/machine learning

Since severe malaria is a complex multi-system illness, diagnosing clinical signs of cerebral malaria can be challenging. Although clinical signs and symptoms are prominent, distinguishing cerebral malaria from other febrile convulsions, meningitis, and encephalitis can be difficult. Prompt treatment initiation is crucial once cerebral malaria is diagnosed or suspected. Clinical observations reveal that coma, hemiparesis, ataxia, and elevated intracranial pressure can develop rapidly from initial malaria symptoms. Apart from misdiagnosis, another obstacle to cerebral malaria detection is the challenge of examining the human brain in vivo. This problem is exacerbated in malaria-endemic areas by a lack of reliable imaging facilities [1]. Table 3 presents the drawbacks of current diagnostic tests for cerebral malaria.

Table 3.

The conventional methods of malaria detection and their major disadvantages

Diagnostic test	Disadvantages	References
Microscopic examination	Need for expert pathologist, results prone to human error	[102]
Rapid diagnostic tests	pfHRP2/3 gene deletions, low sensitivity, cross-reactivity	[103]
PCR	Problematic operation in endemic zones, expensive	[104]
Serology	Unreliable test, improper indication of active infection	[105]
Quantitative buffy coat	Need for expert pathologist, requires expensive fluorescent microscope	[106]
Flow cytometry	Low sensitivity, problematic operation in endemic zones	[107]

Artificial intelligence (AI) systems using deep learning models for parasite identification have been developed [108, 109]. One team developed a convolutional neural network (CNN) model using infected and non-infected cell images from the University of Alabama [110]. This work employed an automatic method of detecting malaria parasites using image processing and compared various machine learning techniques, including Linear SVM, Fine Gaussian SVM, Cosine KNN, Boosted tree, and Subspace KNN. The comparison was based on accuracy, training time, and linearity. The model exhibited a 95% diagnostic success rate [110]. Other authors reported 97.98% efficiency with a CNN utilizing split-transform-merge and channel squeezing-boosting principles [111]. An AI-based object identification system (AIDMAN) for malaria diagnosis has been developed that effectively manages disruptions, with a 97% diagnostic success rate for blood-smear images. This system combines the YOLOv5 model and the Transformer model to perform the entire process from image analysis to malaria diagnosis. A heatmap of the most characteristic cells is generated to reduce interference caused by false-positive cells [112]. Similarly, machine learning (ML) is being used to identify various illnesses, including AD, by integrating information from biological indicators, brain scans, and newly developed instruments for evaluating cognitive abilities. For example, a deep learning (DL) method for initial AD prediction using brain FDG-PET achieved 82% precision and 100% sensitivity at a mean of 75.8 months before a definitive diagnosis was made [113].

Moreover, in sub-Saharan countries like Nigeria, an estimated 206 million inhabitants are served by fewer than 300 neurologists and 131 neurosurgeons. Neurological conditions account for approximately 18% of all medical emergencies. Neurocritical care units (NCCUs) are mostly unavailable in Nigeria, often resulting in poorer prognoses for patients. This situation highlights a significant deficit of trained neurologists and healthcare workers capable of providing specialized neurological care in sub-Saharan countries [114].

Furthermore, AI can incorporate information gathered from novel technologies like language and verbal fluency assessment tools or executive function tests on cognitively intact or moderately impaired patients. In this manner, AI and ML can contribute to the detection of malaria, potentially limiting adverse effects and subsequent development of neurological impairments. However, the availability of these technologies in resource-poor countries remains a significant challenge.

CONCLUSIONS

Cerebral malaria and neurodegenerative disorders represent significant threats to the nervous system, particularly the brain. While various diagnostic and treatment options exist, further advancements are necessary to improve the prognosis of malaria. To fully understand the disease pathophysiology, readily implementable 2D and 3D co-cultures and disease models must be developed. Advanced in vitro bioengineering techniques, such as 3D human brain-specific microvessel models, offer promising avenues for elucidating the mechanisms of cerebral malaria development.

The pathogenesis of malaria affects the brain through multiple mechanisms, including:

1. BBB leakage

2. Neuroinflammation

3. Oxidative stress

4. Physiological manifestations.

These processes intersect with the mechanisms of severe neurodegenerative disorders, potentially leading to long-term neuroinflammatory changes. Early and accurate detection of cerebral malaria is crucial for controlling disease severity and preventing neurological impairments.

Current diagnostic and treatment tools for both cerebral malaria and neurodegenerative diseases lack precision and rapidity. However, the field is on the cusp of transformation, driven by:

1. Development of therapies targeting common pathways

2. Advanced 2D and 3D disease models

3. Artificial intelligence-based diagnostic and prognostic tools.

These innovations promise to enhance our understanding of disease mechanisms, improve early detection, and facilitate the development of more effective treatments. As research progresses, we anticipate significant advancements in managing both cerebral malaria and neurodegenerative disorders, potentially reducing their long-term neurological impacts.

Funding:

No funding was received for this study.

Conflict of interest:

All the authors have no competing interests.

REFERENCES

1. Akide Ndunge OB, Kilian N, Salman MM. Cerebral Malaria and Neuronal Implications of Plasmodium Falciparum Infection: From Mechanisms to Advanced Models. Advanced science (Weinheim, Baden-Wurttemberg, Germany). 2022;9(36):e2202944. https://doi.org/10.1002/advs.202202944.

2. Jiang T, Huang Y, Cheng W, Sun Y, Wei W, Wu K, et al. Multiple single-nucleotide polymorphism detection for antimalarial pyrimethamine resistance via allele-specific pcr coupled with gold nanoparticle-based lateral flow biosensor. Antimicrob Agents Chemother. 2021;65(3):e01063-20. https://doi.org/10.1128/AAC.01063-20.

3. World Health Organization. (March 27, 2023). https://www.who.int/news-room/questions-and-answers/item/malaria?gclid=CjwKCAiAjrarBhAWEiwA2qWdCCcRuoPBQTTXOGjQ7WqY0EC-yoFbDsJFSIGzgnYlpRJ9nV6qR9CMmRoCeHoQAvD_BwE. Accessed on 03.01.2024.

4. Almeida ACG, Kuehn A, Castro AJM, Vitor-Silva S, Figueiredo EFG, Brasil LW, et al. High proportions of asymptomatic and submicroscopic Plasmodium vivax infections in a peri-urban area of low transmission in the Brazilian Amazon. Parasites and Vectors. 2018;11(1):194. https://doi.org/10.1186/s13071-018-2787-7.

5. Storm J, Jespersen JS, Seydel KB, Szestak T, Mbewe M, Chisala NV, et al . CM is associated with differential cytoadherence to brain endothelial cells. EMBO Mol Med. 2019;11(2):e9164. https://doi.org/10.15252/emmm.201809164.

6. Song X, Wei W, Cheng W, Zhu H, Wang W, Dong H, Li J. CM induced by Plasmodium falciparum: Clinical features, pathogenesis, diagnosis, and treatment. Front Cell Infect Microbiol. 2022;12:939532. https://doi.org/10.3389/fcimb.2022.939532.

7. Riggle BA, Manglani M, Maric D, Johnson KR, Lee MH, Neto OLA, et al. CD8+ T cells target cerebrovasculature in children with CM. J Clin Invest. 2020;130(3):1128-38. https://doi.org/10.1172/JCI133474.

8. Idro R, Carter JA, Fegan G, Neville BG, Newton CR. Risk factors for persisting neurological and cognitive impairments following CM. Arch Dis Child. 2006;91(2):142-8. https://doi.org/10.1136/adc.2005.077784.

9. Datta D, Conroy AL, Castelluccio PF, Ssenkusu JM, Park GS, Opoka RO, et al. Elevated cerebrospinal fluid Tau protein concentrations on admission are associated with long-term neurologic and cognitive impairment in Ugandan children with CM. Clin Infect Dis. 2020;70(6):1161-8. https://doi.org/10.1093/cid/ciz325.

10. Rosa-Gonçalves P, Ribeiro-Gomes FL, Daniel-Ribeiro CT. Malaria related neurocognitive deficits and behavioral alterations. Front Cell Infect Microbiol. 2022;12:829413. https://doi.org/10.3389/fcimb.2022.829413.

11. Rantanen LM, Bitar M, Lampinen R, Stewart R, Quek H, Oikari LE, et al An Alzheimer’s Disease Patient-Derived Olfactory Stem Cell Model Identifies Gene Expression Changes Associated with Cognition. Cells. 2022;11(20):3258. https://doi.org/10.3390/cells11203258.

12. Li JX, Liao WZ, Huang ZM, Yin X, Ouyang S, Gu B, Guo XG. Identifying effective diagnostic biomarkers for childhood cerebral malaria in Africa integrating coexpression analysis with machine learning algorithm. Eur J Med Res. 2023;28(1):76. https://doi.org/10.1186/s40001-022-00980-w.

13. Potchen MJ, Kampondeni SD, Seydel KB, Haacke EM, Sinyangwe SS, Mwenechanya M, et al1.5 Tesla magnetic resonance imaging to investigate potential etiologies of brain swelling in pediatric CM. Am J Trop Med Hyg. 2018;98(2):497-504. https://doi.org/10.4269/ajtmh.17-0309.

14. Bannister LH, Sherman IW. (December 2009). Plasmodium. In: Encyclopedia of Life Sciences (ELS), John Wiley and Sons, Ltd, 2009. https://doi.org/10.1002/9780470015902.a0001970.pub2.

15. Stokum JA, Gerzanich V, Simard JM. Molecular pathophysiology of cerebral edema. J Cereb Blood Flow Metab. 2016;36(3):513-38. https://doi.org/10.1177/0271678X15617172.

16. Arastu-Kapur S, Ponder EL, Fonović UP, Yeoh S, Yuan F, Fonović M, et al. Identification of proteases that regulate erythrocyte rupture by the malaria parasite Plasmodium falciparum. Nat Chem Biol. 2008;4(3):203-13. https://doi.org/10.1038/nchembio.70.

17. Yeoh S, O’Donnell RA, Koussis K, Dluzewski AR, Ansell KH, Osborne SA, et al. Subcellular discharge of a serine protease mediates release of invasive malaria parasites from host erythrocytes. Cell. 2007;131(6):1072-83. https://doi.org/10.1016/j.cell.2007.10.049.

18. Chandramohanadas R, Davis PH, Beiting DP, Harbut MB, Darling C, Velmourougane G, et al. Apicomplexan parasites co-opt host calpains to facilitate their escape from infected cells. Science. 2009;324(5928):794-7. https://doi.org/10.1126/science.1171085.

19. Taylor TE, Fu WJ, Carr RA, Whitten RO, Mueller JS, Fosiko NG, et al. Differentiating the pathologies of cerebral malaria by postmortem parasite counts. Nat Med. 2004;10:143-5. https://doi.org/10.1038/nm986.

20. Brown H, Rogerson S, Taylor T, Tembo M, Mwenechanya J, Molyneux M, Turner G. Blood-brain barrier function in cerebral malaria in Malawian children. Am J Trop Med Hyg. 2001;64(3):207-13. https://doi.org/10.4269/ajtmh.2001.64.207.

21. Hawkes M, Elphinstone RE, Conroy AL, Kain KC. Contrasting pediatric and adult CM: The role of the endothelial barrier. Virulence. 2013;4(6):543-55. https://doi.org/10.4161/viru.25949.

22. Wimo A, Aboderin I, Guerchet M, Prince M, Amoakoh-Coleman M, Ezeah P, Lloyd-Sherlock P, Uwakwe R, Mayston R, Akinyemi R, Paddick S-M. Dementia in sub-Saharan Africa. Challenges and opportunities. 2017. https://www.alzint.org/resource/dementia-in-sub-saharan-africa/#:~:text=An%20estimated%202.13%20million%20people,and%207.62%20million%20by%202050.

23. Sweeney MD, Sagare AP, Zlokovic BV. Blood– brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat Rev Neurol. 2018;14(3):133-50. https://doi.org/10.1038/nrneurol.2017.188.

24. Montagne A, Zhao Z, Zlokovic BV. AD: A matter of blood–brain barrier dysfunction? J Exp Med. 2017;214(11):3151-69. https://doi.org/10.1084/jem.20171406.

25. Jambou R, Combes V, Jambou MJ, Weksler BB, Couraud PO, Grau GE. Plasmodium falciparum adhesion on human brain microvascular endothelial cells involves transmigration-like cup formation and induces opening of intercellular junctions. PLOS Pathog. 2010;6(7):e1001021. https://doi.org/10.1371/journal.ppat.1001021.

26. Lima MN, Freitas RJRX, Passos BABR, Darze AMG, Castro-Faria-Neto HC, Maron-Gutierrez T. (2021). Neurovascular Interactions in Malaria. Neuroimmunomodulation. 2021;28(3):108-17. https://doi.org/10.1159/000515557.

27. Kany S,Vollrath JT,Relja B. Cytokines in inflammatory disease. Int J Mol Sci. 2019;20(23):6008. https://doi.org/10.3390/ijms20236008.

28. Koupenova M, Clancy L, Corkrey HA, Freedman JE. Circulating platelets as mediators of immunity, inflammation, and thrombosis. Circ Res. 2018;122(2):337-51. https://doi.org/10.1161/CIRCRESAHA.117.310795.

29. Berendt AR, Simmons DL, TanseyJ, Newbold CI, Marsh K. Intercellular adhesion molecule-1 is an endothelial cell adhesion receptor for Plasmodium falciparum. Nature. 1989;341(6237):57-59. https://doi.org/10.1038/341057a0.

30. Adams S, Brown H, Turner G. Breaking down the blood–brain barrier: signaling a path to cerebral malaria? Trends parasitol. 2002;18(8):360-6. https://doi.org/10.1016/s1471-4922(02)02353-x.

31. Crotti A, Ransohoff RM. Microglial physiology and pathophysiology: Insights from genome-wide transcriptional profiling. Immunity. 2016;44(3):505-15. https://doi.org/10.1016/j.immuni.2016.02.013.

32. Combes V, El-Assaad F, Faille D, Jambou R, Hunt NH, Grau GE. Microvesiculation and cell interactions at the brain–endothelial interface in CM pathogenesis. Progress in Neurobiology. 2010;91(2):140-51. https://doi.org/10.1016/j.pneurobio.2010.01.007.

33. Bakmiwewa SM, Weiser S, Grey M, Heng B, Guillemin GJ, Ball HJ, Hunt NH. Synergistic induction of CXCL10 by interferon-gamma and lymphotoxin-alpha in astrocytes: Possible role in cerebral malaria. Cytokine. 2016;78:79-86. https://doi.org/10.1016/j.cyto.2015.11.024.

34. Medana IM, Day NP, Roberts R, Sachanonta N, Turley H, Pongponratn E, et al. Induction of the vascular endothelial growth factor pathway in the brain of adults with fatal falciparum malaria is a non-specific response to severe disease. Histopathology. 2010;57(2):282-94. https://doi.org/10.1111/j.1365-2559.2010.03619.x.

35. Medana IM, Chaudhri G, Chan-Ling T, Hunt NH. Central nervous system in CM: “Innocent bystander” or active participant in the induction of immunopathology? Immunol Cell Biol. 2001;79(2):101-20. https://doi.org/10.1046/j.1440-1711.2001.00995.x.

36. Heneka MT, Carson MJ, El Khoury JE, Landreth GE, Brosseron F, Feinstein DL, et al. Neuroinflammation in AD. Lancet Neurol. 2015;14(4):388-405. https://doi.org/10.1016/S1474-4422(15)70016-5.

37. Bis JC, Jian X, Kunkle BW, Chen Y, Hamilton-Nelson KL, Bush WS, et al. Whole exome sequencing study identifies novel rare and common Alzheimer’s-associated variants involved in immune response and transcriptional regulation. Mol Psychiatry. 2020;25(8):1859-75. https://doi.org/10.1038/s41380-018-0112-7.

38. Pimenova AA, Raj T, Goate AM. Untangling genetic risk for AD. Biol Psychiatry. 2018;83(4):300-10. https://doi.org/10.1016/j.biopsych.2017.05.014.

39. Woodburn SC, Bollinger JL, Wohleb ES. The semantics of microglia activation: Neuroinflammation, homeostasis, and stress. J Neuroinflammation. 2021;18(1):258. https://doi.org/10.1186/s12974-021-02309-6.

40. Mishra SK, Newton CR. Diagnosis and management of the neurological complications of falciparum malaria. Nat Rev Neurol. 2009;5(4):189-98. https://doi.org/10.1038/nrneurol.2009.23.

41. Parsons AL, Bucknor EM, Castroflorio E, Soares TR, Oliver PL, Rial D. The interconnected mechanisms of oxidative stress and neuroinflammation in epilepsy. Antioxidants. 2022;11(1):157. https://doi.org/10.3390/antiox11010157.

42. Montagne A, Nation DA, Sagare AP, Barisano G, Sweeney MD, Chakhoyan A, et al. APOE4 leads to blood–brain barrier dysfunction predicting cognitive decline. Nature. 2020;581(7806):71-6. https://doi.org/10.1038/s41586-020-2247-3.

43. Kassa FA, Van Den Ham K, Rainone A, Fournier S, Boilard E, Olivier M. Absence of apolipoprotein E protects mice from CM. Sci Rep. 2016;6(1):33615. https://doi.org/10.1038/srep33615.

44. Cai W, Li L, Sang S, Pan X, Zhong C. Physiological Roles of β-amyloid in Regulating Synaptic Function: Implications for AD Pathophysiology. Neuroscie Bull. 2023;39(8):1289-308. https://doi.org/10.1007/s12264-022-00985-9.

45. Huang YA, Zhou B, Wernig M., Südhof TC. ApoE2, ApoE3, and ApoE4 differentially stimulate APP transcription and Aβ secretion. Cell. 2017;168(3):427-41.e21. https://doi.org/10.1016/j.cell.2016.12.044.

46. Higginbotham L, Ping L, Dammer EB, Duong DM, Zhou M, Gearing M, et al. Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer’s disease. Sci Adv. 2020;6(43):33087358. https://doi.org/10.1126/sciadv.aaz9360.

47. Sasayama D, Hattori K, Yokota Y, Matsumura R, Teraishi T, Yoshida S, Kunugi H. Increased apolipoprotein E and decreased TNF-α in the cerebrospinal fluid of nondementedAPOE-ε4 carriers. Neuropsychopharmacol Rep. 2020;40(2):201-5. https://doi.org/10.1002/npr2.12110.

48. Liao F, Li A, Xiong M, Bien-Ly N, Jiang H, Zhang Y, et al. Targeting of nonlipidated, aggregated apoE with antibodies inhibits amyloid accumulation. J Clin Invest. 2018;128(5):2144-55. https://doi.org/10.1172/JCI96429.

49. Fujioka H, Phelix CF, Friedland RP, Zhu X , Perry EA, Castellani RJ, Perry G. Apolipoprotein E4 prevents growth of malaria at the intraerythrocyte stage: implications for differences in racial susceptibility to Alzheimer’s disease. JHCPU. 2013;24(4 Suppl):70. https://doi.org/10.1353/hpu.2014.0009.

50. Lima-Cooper G, Ouma BJ, Datta D, Bond C, Soto AA, Conroy AL, et al. Apolipoprotein-E4: risk of severe malaria and mortality and cognitive impairment in pediatric cerebral malaria. Pediatr Res. 2024; 96:89-96. https://doi.org/10.1038/s41390-023-02912-8.

51. Kioko M, Mwangi S, Njunge J, Berkley J, Bejon P, Abdi A. Linking cerebral malaria pathogenesis to APOE-mediated amyloidosis. 2023 (preprint). https://doi.org/10.21203/rs.3.rs-3512412/v1.

52. Barron M, Gartlon J, Dawson LA, Atkinson PJ, Pardon M-C. A state of delirium: Deciphering the effect of inflammation on tau pathology in Alzheimer’s disease. Exp Gerontol. 2017;94:103-7. https://doi.org/10.1016/j.exger.2016.12.006.

53. Brunden KR, Trojanowski JQ, Lee VM-Y. Advances in Tau-focused drug discovery for Alzheimer’s disease and related tauopathies. Nat Rev Drug Discov. 2009;8(10):783-93. https://doi.org/10.1038/nrd2959.

54. Yamagishi J, Natori A, Tolba ME, Mongan AE, Sugimoto C, Katayama T, et al. Interactive transcriptome analysis of malaria patients and infecting Plasmodium falciparum. Genome Res. 2014;24(9):1433-44. https://doi.org/10.1101/gr.158980.113.

55. Cabantous S, Doumbo O, Poudiougou B, Louis L, Barry A, Oumar AA, et al. Gene expression analysis reveals genes common to CM and neurodegenerative disorders. J Infect Dis. 2017;216(6):771-5. https://doi.org/10.1093/infdis/jix359.

56. Nakayama K, Qi J, Ronai Z. The ubiquitin ligase Siah2 and the hypoxia response. Mol Cancer Res. 2009;7(4):443-51. https://doi.org/10.1158/1541-7786.MCR-08-0458.

57. Matsuda S, Kitagishi Y, Kobayashi M. Function and characteristics of PINK1 in mitochondria. Oxid Med Cell Longev. 2013;601587. https://doi.org/10.1155/2013/601587.

58. Cushion TD, Paciorkowski AR, Pilz DT, Mullins JG, Seltzer LE, Marion RW, et al. De novo mutations in the beta-tubulin gene TUBB2A cause simplified gyral patterning and infantile-onset epilepsy. Am J Hum Genet. 2014;94(4):634-41. https://doi.org/10.1016/j.ajhg.2014.03.009.

59. Sender R, Fuchs S, Milo R. Are we really vastly outnumbered? revisiting the ratio of bacterial to host cells in humans. Cell. 2016;164(3):337-40. https://doi.org/10.1016/j.cell.2016.01.013.

60. LeBlanc JG., MilaniC, de Giori GS, Sesma F, van Sinderen D, Ventura M. Bacteria as vitamin suppliers to their host: A gut microbiota perspective. Cur Opin Biotechnol. 2013;24(2):160-8. https://doi.org/10.1016/j.copbio.2012.08.005.

61. Dodd D, Spitzer MH, Van Treuren W, Merrill BD, Hryckowian AJ, Higginbottom SK, et al. A gut bacterial pathway metabolizes aromatic amino acids into nine circulating metabolites. Nature. 2017;551(7682):648-52. https://doi.org/10.1038/nature24661.

62. Rutsch A, Kantsjö JB, Ronchi F. The gut-brain axis: How microbiota and host inflammasome influence brain physiology and pathology. Front Immunol. 2020;11:604179. https://doi.org/10.3389/fimmu.2020.604179.

63. Vogt NM, Kerby RL, Dill-McFarland KA, Harding SJ, Merluzzi AP, Johnson SC, et al. Gut microbiome alterations in AD. Sci Rep. 2017;7(1): 13537. https://doi.org/10.1038/s41598-017-13601-y.

64. Giau VV, Wu SY, Jamerlan A, An SSA, Kim SY, Hulme J. Gut microbiota and their neuroinflammatory implications in AD. Nutrients. 2018;10(11):1765. https://doi.org/10.3390/nu10111765.

65. Parker A, Fonseca S, Carding SR. Gut microbes and metabolites as modulators of blood–brain barrier integrity and brain health. Gut Microbes. 2020;11(2):135-57. https://doi.org/10.1080/19490976.2019.1638722.

66. Alloo J,Leleu I,Grangette C,PiedS.Parasiteinfections, neuroinflammation, and potential contributions of gut microbiota. Front Immunol. 2022;13:1024998. https://doi.org/10.3389/fimmu.2022.1024998.

67. Villarino NF, LeCleir GR, Denny JE, Dearth SP, Harding CL, Sloan SS, et al. Composition of the gut microbiota modulates the severity of malaria. Proc Natl Acad Sci USA. 2016;113(8):2235-40. https://doi.org/10.1073/pnas.1504887113.

68. Luu M, Weigand K, Wedi F, Breidenbend C, Leister H, Pautz S., et al. Regulation of the effector function of CD8+ T cells by gut microbiota-derived metabolite butyrate. Sci Rep. 2018;8(1):14430. https://doi.org/10.1038/s41598-018-32860-x.

69. Duarte-Silva E, Morais LH, Clarke G, Savino W, Peixoto C. Targeting the gut microbiota in Chagas disease: What do we know so far? Front Microbiol. 2020;11:585857. https://doi.org/10.3389/fmicb.2020.585857.

70. Pohanka M. Role of oxidative stress in infectious diseases. A review. Folia Microbiol. 2013;58(6):503-13. https://doi.org/10.1007/s12223-013-0239-5.

71. Medana IM, Esiri MM. Axonal damage: A key predictor of outcome in human CNS diseases. Brain. 2003;126(3):515-30. https://doi.org/10.1093/brain/awg061.

72. Eckert D, Rapp F, Tsedeke AT, Molendowska J, Lehn R, Langhans M, et al. ROS- and radiation source-dependent modulation of leukocyte adhesion to primary microvascular endothelial cells. Cells. 2021;11(1):72. https://doi.org/10.3390/cells11010072.

73. Chung HY, Cesari M, Anton S, Marzetti E, Giovannini S, Seo AY, et al. Molecular inflammation: Underpinnings of aging and age-related diseases. Ageing Res Rev. 2009;8(1):18-30. https://doi.org/10.1016/j.arr.2008.07.002.

74. Huang WJ, Zhang X, Chen WW. Role of oxidative stress in Alzheimer’s disease (Review). Biomed rep. 2016;4:519-22. https://doi.org/10.3892/br.2016.630.

75. Franke-Fayard B, Fonager J, Braks A, Khan SM, Janse CJ. Sequestration and tissue accumulation of human malaria parasites: Can we learn anything from rodent models of malaria? PLOS Pathog. 2010;6(9):e1001032. https://doi.org/10.1371/journal.ppat.1001032.

76. Oddo A, Peng B, Tong Z, wie Y, Tong WY, Thissen H, Voelcker NH. Advances in microfluidic blood– brain barrier (BBB) models. Trends Biotechnol. 2019;37(12):1295-314. https://doi.org/10.1016/j.tibtech.2019.04.006.

77. Song Y, Cai X, Du D, Dutta P, Lin Y. Comparison of blood–brain barrier models for in vitro biological analysis: One cell type vs three cell types. ACS Appl Bio Mater. 2019;2(3):1050-5. https://doi.org/10.1021/acsabm.8b00654.

78. Santa-Maria AR, Walter FR, Figueiredo R, Kincses A, Vigh JP, Heymans M, et al. Flow induces barrier and glycocalyx-related genes and negative surface charge in a lab-on-a-chip human blood–brain barrier model. J Cereb Blood Flow Metab. 2021;41(9):2201-15. https://doi.org/10.1177/0271678X21992638.

79. Wassmer SC, Grau GER. Severe malaria: What’s new on the pathogenesis front? Int J Parasitol. 2017;47(2-3):145-52. https://doi.org/10.1016/j.ijpara.2016.08.002.

80. Chang Y, Kim J, Park H, Choi H, Kim J. Modelling neurodegenerative diseases with 3D brain organoids. Biol Rev Cambridge Philos Soc. 2020;95(5):1497-509. https://doi.org/10.1111/brv.12626.

81. Harbuzariu A, Pitts S, Cespedes JC, Harp KO, Nti A, Shaw AP, et al. Modelling heme-mediated brain injury associated with cerebral malaria in human brain cortical organoids. Sci Rep. 2019;9(1):19162. https://doi.org/10.1038/s41598-019-55631-8.

82. Białkowska K, Komorowski P, Bryszewska M, Miłowska K. Spheroids as a type of three-dimensional cell cultures-examples of methods of preparation and the most important application. Int J Mol Sci. 2020;21(17):32872135. https://doi.org/10.3390/ijms21176225.

83. Haston KM, Finkbeiner S. Clinical trials in a dish: The potential of pluripotent stem cells to develop therapies for neurodegenerative diseases. Annu Rev Pharmacol Toxicol. 2016;56:489-510. https://doi.org/10.1146/annurev-pharmtox-010715-103548.

84. Aikawa M, Brown AE, Smith CD, Tegoshi T, Howard RJ, Hasler TH, et al. Plasmodium coatneyi-infected rhesus monkeys: a primate model for human cerebral malaria. Memórias do Instituto Oswaldo Cruz. 1992;87(Suppl 3):443-7. https://doi.org/10.1590/S0074-02761992000700074.

85. Langhorne J, Buffet P, Galinski M, Good M, Harty J, Leroy D, et al. The relevance of non-human primate and rodent malaria models for humans. Malar J. 2011;10:1-4. https://doi.org/10.1186/1475-2875-10-23.

86. Craig AG, Grau GE, Janse C, Kazura JW, Milner D, Barnwell JW, et al. The role of animal models for research on severe malaria. PLoS pathog. 2012;8(2):e1002401. https://doi.org/10.1371/journal.ppat.1002401.

87. Adams Y, Clausen AS, Jensen PØ, Lager M, Wilhelmsson P, Henningson AJ, et al. 3D blood-brain barrier-organoids as a model for Lyme neuroborreliosis highlighting genospecies dependent organotropism. Iscience. 2023;26(1). https://doi.org/10.1016/j.isci.2022.105838.

88. Bernabeu M, Howard C, Zheng Y, Smith JD. Bioengineered 3D microvessels for investigating Plasmodium falciparum pathogenesis. Trends parasitol. 2021;37(5):401-3. https://doi.org/10.1016/j.pt.2020.12.008.

89. Durante MA, Kurtenbach S, Sargi ZB, Harbour JW, Choi R, Kurtenbach S, et al. Single-cell analysis of olfactory neurogenesis and differentiation in adult humans. Nat Neuroscie. 2020;23(3):323-6. https://doi.org/10.1038/s41593-020-0587-9.

90. Gómez-Virgilio L, Luarte A, Ponce DP, Bruna BA, Behrens MI. Analyzing olfactory neuron precursors non-invasively isolated through NADH FLIM as a potential tool to study oxidative stress in AD. Int J Mol Sci. 2021;22(12):6311. https://doi.org/10.3390/ijms22126311.

91. Waknine-Grinberg JH, Even-Chen S, Avichzer J, Turjeman K, Bentura-Marciano A, Haynes RK, et al. Glucocorticosteroids in nano-sterically stabilized liposomes are efficacious for elimination of the acute symptoms of experimental CM. PLOS ONE. 2013;8(8):e72722. https://doi.org/10.1371/journal.pone.0072722.

92. Patel OPS, Beteck RM, Legoabe LJ. Exploration of artemisinin derivatives and synthetic peroxides in antimalarial drug discovery research. Eur J Med Chem. 2021;213:113193. https://doi.org/10.1016/j.ejmech.2021.113193.

93. Wang P, Tian X, Tang J, Duan X, Wang J, Cao H, et al. Artemisinin protects endothelial function and vasodilation from oxidative damage via activation of PI3K/Akt/eNOS pathway. Exp Gerontol 2021, 147, 111270. https://doi.org/10.1016/j.exger.2021.111270.

94. Morris CA, Tan B, Duparc S, Borghini-Fuhrer I, Jung D, Shin CS, Fleckenstein L. Effects of body size and gender on the population pharmacokinetics of artesunate and its active metabolite dihydroartemisinin in pediatric malaria patients. Antimicrob Agents Chemother. 2013;57(12):5889-900. https://doi.org/10.1128/AAC.00635-13.

95. Ludewig-Klingner AK, Michael V, Jarek M, Brinkmann H, Petersen J. Distribution and Evolution of Peroxisomes in Alveolates (Apicomplexa, Dinoflagellates, Ciliates). Genome Biol Evol. 2018;10(1):1-13. https://doi.org/10.1093/gbe/evx250.

96. Watanabe K, Tanaka M, Yuki S, Hirai M, Yamamoto Y. How is edaravone effective against acute ischemic stroke and amyotrophic lateral sclerosis? J Clin Biochem Nutr. 2018;62(1):20-38. https://doi.org/10.3164/jcbn.17-62.

97. Prasad K, Garner P. Steroids for treating cerebral malaria. CDSR. 1996;2019(5). https://doi.org/10.1002/14651858.CD000972.

98. Warrell DA, Looareesuwan S, Warrell MJ, Kasemsarn P, Intaraprasert R, Bunnag D, et al. Dexamethasone proves deleterious in cerebral malaria. A double-blind trial in 100 comatose patients. N Engl J Med. 1982;306:313-9. https://doi.org/10.1056/NEJM198202113060601.

99. Lell B, Köhler C, Wamola B, Olola CH, Kivaya E, Kokwaro G, et al. Pentoxifylline as an adjunct therapy in children with cerebral malaria. Malar J. 2010;9:1-6. https://doi.org/10.1186/1475-2875-9-368.

100. De Souza JB, Okomo U, Alexander ND, Aziz N, Owens BM, Kaur H, et al. Oral activated charcoal prevents experimental CM in mice and in a randomized controlled clinical trial in man did not interfere with the pharmacokinetics of parenteral artesunate. PLOS ONE. 2010;5(4):e9867. https://doi.org/10.1371/journal.pone.0009867.

101. Mota S, Bensalel J, Park DH, Gonzalez S, Rodriguez A, Gallego-Delgado J. Treatment reducing endothelial activation protects against experimental cerebral malaria. Pathogens. 2022;11(6):643. https://doi.org/10.3390/pathogens11060643.

102. Heide J, Vaughan KC, Sette A, Jacobs T, Schulze Zur Wiesch J. Comprehensive review of human Plasmodium falciparum-specific CD8+ T cell epitopes. Front Immunol. 2019;10:397. https://doi.org/10.3389/fimmu.2019.00397.

103. Cunningham J, Jones S, Gatton ML, Barnwell JW, Cheng Q, Chiodini PL, et al. A review of the WHO malaria rapid diagnostic test product testing programme (2008–2018): Performance, procurement and policy. Malar J. 2019;18(1):387. https://doi.org/10.1186/s12936-019-3028-z.

104. Eshag HA, Elnzer E, Nahied E, Talib M, Mussa A, Muhajir AEMA, et al. Molecular epidemiology of malaria parasite amongst patients in a displaced people’s camp in Sudan. Trop Med Int Health. 2020; 48:3. https://doi.org/10.1186/s41182-020-0192-3.

105. Oviedo A, Knipes A, Worrell C, Fox LM, Desir L, Fayette C, et al. Combination of serological, antigen detection, and DNA data for Plasmodium falciparum provides robust geospatial estimates for malaria transmission in Haiti. Sci Rep. 2020;10(1):8443. https://doi.org/10.1038/s41598-020-65419-w.

106. Siciliano G, Alano P. Enlightening the malaria parasite life cycle: Bioluminescent Plasmodium in fundamental and applied research. Front Microbiol. 2015;6:391. https://doi.org/10.3389/fmicb.2015.00391.

107. Khartabil, T. A., de Rijke, Y. B., Koelewijn, R., van Hellemond, J. J., Russcher, H. Fast detection and quantification of Plasmodium species infected erythrocytes in a non-endemic region by using the Sysmex XN-31 analyzer. Malar J. 2022;21(1):119. https://doi.org/10.1186/s12936-022-04147-0.

108. Pattanaik PA, Mittal M, Khan MZ, Panda SN. Malaria detection using deep residual networks with mobile microscopy. J King Saud Univ - Comput Inf Sci. 2022;34(5):1700-5. https://doi.org/10.1016/j.jksuci.2020.07.003.

109. Li D, Ma Z. Residual attention learning network and SVM for malaria parasite detection. Multimed Tool. 2022; Appl.81:10935-60. https://doi.org/10.1007/s11042-022-12373-6.

110. Olugboja A, Wang Z. Malaria parasite detection using different machine learning classifier. IEEE Publications. 2017;246-50.https://doi.org/10.1109/ICMLC.2017.8107772.

111. Khan SH, Shah NS, Nuzhat R, Majid A, Alquhayz H, Khan A. Malaria parasite classification framework using a novel channel squeezed and boosted CNN. Microscopy. 2022;71(5):271-82. https://doi.org/10.1093/jmicro/dfac027.

112. Liu R, Liu T, Dan T, Yang S, Li Y, Luo, B., et al. AIDMAN: An AI-based object detection system for malaria diagnosis from smartphone thin-blood-smear images. Patterns. 2023;4(9):100806. https://doi.org/10.1016/j.patter.2023.100806.

113. Ding Y, Sohn JH, Kawczynski MG, Trivedi H, Harnish R, Jenkins NW, et al. A deep learning model to predict a diagnosis of Alzheimer disease by using 18F-FDG PET of the brain. Radiology. 2019;290(2):456-64. https://doi.org/10.1148/radiol.2018180958.

114. Komolafe MA, Idowu AO, Peter ME, Oyinlola HW, Sanusi AA, Balogun SA, et al. Neurocritical Care in Nigeria. West Afr J Med. 2023;40(6):630-3. PMID: 37390330.