alexa Alterations in the Brain Transcriptome in Plasmodium Berghei ANKA Infected Mice | OMICS International
E-ISSN: 2314-7326
P-ISSN: 2314-7334
Journal of Neuroinfectious Diseases
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Alterations in the Brain Transcriptome in Plasmodium Berghei ANKA Infected Mice

Mahalia S. Desruisseaux1,2* Dumitru A. Iacobas3 Sanda Iacobas3 Shankar Mukherjee1 Louis M.Weiss1,2 Herbert B. Tanowitz1,2 and David C. Spray2,3

1Department of Pathology, Albert Einstein College of Medicine, Bronx, NY 10461, USA

2Department of Medicine, Albert Einstein College of Medicine, Bronx, NY 10461, USA

3The Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA

Corresponding Author:
Mahalia S. Desruisseaux
Department of Pathology, Albert Einstein
College of Medicine, Bronx, NY 10461, USA
E-mail: [email protected]

Received date: 31 August 2010; Accepted date: 18 September 2010

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We have used cDNA microarrays to compare gene expression profiles in brains from normal mice to those infected with the ANKA strain of Plasmodium berghei, a model of cerebral malaria. For each of three brains in each group, we computed ratios of all quantifiable genes with a composite reference sample and then computed ratios of gene expression in infected brains compared to untreated controls. Of the almost 12,000 unigenes adequately quantified in all arrays, approximately 3% were significantly downregulated (P < 0.05, ≥ 50% fold change) and about 7% were upregulated. Upon inspection of the lists of regulated genes, we identified a high number encoding proteins of importance to normal brain function or associated with neuropathology, including genes that encode for synaptic proteins or genes involved in cerebellar function as well as genes important in certain neurological diseases such as Alzheimer’s disease or autism. These results emphasize the important impact of malarial infection on gene expression in the brain and provide potential biomarkers that may provide novel therapeutic targets to ameliorate the neurological sequelae of this infection.


malaria; neurobiology; gene regulation; Plasmodium berghei; mouse models; vascular disease


A large study in sub-Saharan Africa reported that almost 50% of malarial patients exhibited neurological deficits [15] encompassing a number of symptoms, including ataxia, seizures, hemiplegia, and eventually coma and death [13, 15,16]. In addition, greater than 20% of children who survive an episode of cerebral malaria sustain persistent cognitive deficits, which can include memory impairment, visuospatial deficits, and psychiatric disorders as well as motor coordination dysfunction [2, 3, 6,12,20]. While the precise etiology of cerebral malaria has not fully been elucidated, recently vasculopathy has been recognized as contributory to mortality during cerebral malaria [5].We and others previously demonstrated that experimental cerebral malaria is associated with impairment of blood flow to the cerebral microvasculature, and that this directly correlated with neuronal and axonal damage [18, 31]. Impairment of the cerebral blood flow and associated axonal damage has also been observed in children with cerebral malaria [1, 35]. In addition, although cerebral malaria affects the vasculature, extensive immunological and inflammatory effects occur within the nervous system [4]. In fact, recent studies intimate that the development of deficits in human cerebral malaria is a complex issue which involves the progression of metabolic and physiologic processes in several regions of the brain [19].

Microarray analysis of differentially expressed genes offers the possibility to search for pathways responsible for disease in a broad, unbiased approach. Using such a strategy, a number of authors have previously identified interferonregulated genes as prominently altered in brains of mice that are susceptible to cerebral malaria [33], with differential expression in mouse strains that are either susceptible or resistant to cerebral malaria [9, 25]. Most recently, Lovegrove et al. [24] identified neuronal apoptosis as another pathway that was differentially regulated. Although many genes show strain-specific expression and there are numerous differences between mouse models and human disease, the utility of this novel approach for appreciating alterations in expression of neural genes was highlighted in the accompanying commentary by John [17].

We have recently obtained evidence for cognitive deficits in mice infected with the ANKA strain of Plasmodium berghei, a well-studied mouse model of cerebral malaria [8, 10]. Because previous studies had observed such small numbers of altered genes in brain or had been focused on changes occurring in other tissues, we undertook the experiments described here, in which multiple biological replicas were used to provide statistically meaningful datasets of up- and downregulated genes. Our findings indicate profound changes in gene expression in the brains of infected animals, both with regard to total number of affected genes and the multiple signaling pathways that they encompass. Particularly surprising was the extraordinarily high number of affected genes that are associated with neurological disease. We conclude from this study that infection of mice with a Plasmodium strain which causes cerebral malaria leads to large-scale gene expression changes in the brain, emphasizing that the resulting disease is fundamentally neurological and identifying putative neural targets toward which therapy might be directed.

Materials and Methods

Infection of mice

Experiments were performed with the approval of the Institutional Animal Care and Use Committee of the Albert Einstein College of Medicine. Four- to five-week old C57BL/6 female mice (Jackson laboratory, Bar harbor, ME) were either infected with Plasmodium berghei ANKA (PbA) or left uninfected for comparison. Blood containing either 5 × 105 red blood cells (RBCs) parasitized with PbA or uninfected blood was diluted in PBS, and 200 microliters were injected via the intraperitoneal route. The mice were then separated into two groups of infected or uninfected mice. Parasitemia, or the percentage of parasitized RBCs, was evaluated by examining Giemsa stained blood smears on day 6 postinfection (PI). On day 6 PI, mice were rapidly euthanized using carbon dioxide and the brains were harvested, frozen in liquid nitrogen, and then stored at −80◦C for future analysis.

RNA extraction and hybridization

We used a previously published protocol [14] and a composite reference RNA sample (R) prepared in sufficient quantity for the entire experiment from ten adult mouse tissues (aorta, brain, heart, kidney, liver, lung, ovary/testicles, spleen, and stomach—equal amounts from males and females). This combination of source tissues provided a high diversity of genes expressed in the midrange of the detection system for the AECOM mouse cDNA microarrays. Briefly, 60 μg total RNA, extracted in Trizol® (Invitrogen, Carlsbad, CA) from brains of three infected (I) and three control (C) mice, purified with RNeasy® mini kit (Qiagen, Valencia, CA), were reverse transcribed into cDNA incorporating fluorescent Cy3- dUTP. The composite reference was reverse transcribed to incorporate Cy5-dUTP. Each of the six Cy3-labeled brain extracts was cohybridized overnight at 50◦C against the Cy5-labeled reference with 32 k 70-mer oligonucleotide mouse microarrays produced by the Microarray Facility of the Albert Einstein College of Medicine (platform described in cgi?acc=GPL5371). After hybridization, the slides were washed at room temperature, using solutions containing 0.1% sodium dodecyl sulfate (SDS) and 1% SSC (3M NaCl + 0.3M sodium citrate) to remove the nonhybridized cDNAs.

Acquisition, filtering, and normalization

All microarrays were scanned with an Axon GenePix® 4000B scanner1 and data acquired through GenePixTM Pro 6.0 software2. Spots with substantial local imperfections (customarily flagged by the acquisition program), those for which the medians of the foreground signals were not at least twice as high as the medians of the background signals in both channels, and those with saturated pixels were eliminated from the analysis to avoid inadequate quantification. Background-subtracted signals were normalized through an iterative algorithm, alternating within-array normalization with interarray normalization until the average corrected ratio differed by less than 5% in subsequent steps. Normalized relative expression levels were then organized into redundancy groups, each composed of all spots probing the same gene and each group then represented by the weighted average of the individual spot values.

Detection of differentially expressed genes

Detection of differentially expressed genes relied on both absolute >1.5x fold-change and < 0.05 P-value of the heteroscedastic t-test applied to the means of the background subtracted normalized fluorescence values in the four biological replicas of the compared transcriptomes. The P-values (two samples, unequal variance) were computed with a Bonferroni-type correction applied to the redundancy groups [14].

Result and Discussion

Data complying with the “Minimum Information About Microarray Experiments” (MIAMEs) were deposited in the National Center for Biotechnology Information Gene Expression Omnibus database (http://www.ncbi.nlm.nih. gov/geo/query/acc.cgi?acc=GSE24086). Of the 11,669 genes whose expression was adequately quantified on all arrays, 335 (2.87%) were significantly downregulated and 793 (6.90%) upregulated in infected mouse brain. These differentially expressed genes, along with their expression ratios and P-values are listed in Table 1.

B. GO terms downregulated in malarial brain
GOID GO name Ttype Number changed local Number measured local Number in GO local Percent changed local Z Score Permuted P
1584 rhodopsin-like receptor activity F 16 107 537 14.95327 3.388 0.001
3674 molecular function F 1 22 673 4.545455 2.383 0.024
4888 transmembrane receptor activity F 1 15 88 6.666667 2.884 0.007
4930 G-protein coupled receptor activity F 3 25 469 12 3.546 0
4984 olfactory receptor activity F 28 193 1106 14.50777 2.61 0.013
5125 cytokine activity F 5 21 162 23.80952 2.449 0.018
6338 chromatin remodeling P 3 14 37 21.42857 2.326 0.042
7156 homophilic cell adhesion P 7 37 122 18.91892 2.058 0.038
7166 cell  surface  receptor-linked  signal transduction P 3 13 140 23.07692 2.777 0.012
7186 G-protein coupled receptor protein signaling pathway P 49 355 1776 13.80282 2.291 0.024
7608 sensory perception of smell P 27 192 1095 14.0625 2.385 0.025
9968 negative regulation of signal trans-duction P 1 15 34 6.666667 2.378 0.019
16503 pheromone receptor activity F 6 25 150 24 2.572 0.022
42742 defense response to bacterium P 5 12 69 41.66667 3.442 0.006
50896 response to stimulus P 28 207 1194 13.52657 2.735 0.006
B. GO terms downregulated in malarial brain
16791 phosphoricmonoesteractivity hydrolase F 1 18 12 5.555555 2.388 0.028
5925 focal adhesion C 3 14 30 21.42857 3.437 0.009
30141 secretory granule C 3 15 32 20 2.503 0.032
16323 basolateral plasma membrane C 2 18 32 11.11111 3.157 0.01
3746 translation elongation factor activity F 3 14 32 21.42857 3.437 0.016
16820 “hydrolase activity\, acting on acid anhydrides\, catalyzing transmem- brane movement of substances” F 2 13 33 15.38461 0.805 0.455
6333 chromatin assembly or disassembly P 2 16 37 12.5 4.666 0
7179 transforming growth factor beta receptor signaling pathway P 1 10 41 10 1.525 0.185
151 ubiquitin ligase complex C 1 15 45 6.666667 1.441 0.155
6874 calcium ion homeostasis P 3 18 47 16.66667 2.892 0.03
43066 negative regulation of apoptosis P 3 23 57 13.04348 2.753 0.014
785 chromatin C 2 23 95 8.695652 2.797 0.015
3682 chromatin binding F 5 48 110 10.41667 2.286 0.041
786 nucleosome C 4 29 115 13.7931 2.805 0.019
42981 regulation of apoptosis P 1 33 116 3.030303 1.601 0.139
4721 phosphoprotein phosphatase activity F 3 12 120 25 2.601 0.025
7001 chromosome organization and bio-genesis (sensu Eukaryota) P 4 29 124 13.7931 3.221 0.001
17111 nucleoside-triphosphatase activity F 1 31 125 3.225806 2.344 0.019
6334 nucleosome assembly P 6 36 125 16.66667 4.029 0.001
5694 chromosome C 4 58 166 6.896552 2.148 0.034
6629 lipid metabolic process P 5 66 217 7.575758 3.019 0.005
74 regulation of progression through cell cycle P 2 43 248 4.651163 2.346 0.028
6412 translation P 2 67 459 2.985075 2.199 0.036
5488 binding F 4 107 541 3.738318 3.217 0.003
3723 RNA binding F 10 138 544 7.246377 2.481 0.017
5739 mitochondrion C 18 276 813 6.521739 2.455 0.029
16787 hydrolase activity F 24 315 1273 7.619048 2.344 0.019
3676 nucleic acid binding F 11 245 1299 4.489796 2.664 0.008
5737 cytoplasm C 21 501 1495 4.191617 2.591 0.01
3677 DNA binding F 18 348 1725 5.172414 1.697 0.074
5622 intracellular C 22 567 1962 3.88007 2.935 0.008
46872 metal ion binding F 29 638 2173 4.545455 2.567 0.012
5634 nucleus C 67 1268 3680 5.283912 2.993 0.003
5515 protein binding F 84 1678 4425 5.00596 2.809 0.006

Table 1: Gene ontology terms of altered genes in CM brains.

When pathways of regulated genes were analyzed using GenMapp software, the most prominent pathways of upregulated genes (Table 1A) were those related to rhodopsin like receptors and related categories of olfactory, G-protein coupled, hormone and transmembrane receptors, and perception of smell, including the beta adrenergic receptor (Adrb3), muscarinic receptors Chrm2 and Chrm3, the orexin receptor Hetr1, the H1 histamine receptors Hrh1 and Htr1a1, the prostaglandin receptor Ptgfr, and the vomeronasal receptors V1rc20, V1rc8, V1rel18, and v1rd13. Other GO terms with disproportionately high number of regulated genes were cytokine production (Tnfs15, Inhbb, Cdlb1, Il17f, Cdld1, Nod1, and Spin), voltage gated chloride channels (Clic2, Clic4, Clic5), chromatin remodeling (Mta2, Smarcc1, Suv39h2, Suv39h1, Nasp), and genes related to defense and acute phase response (Fn1m Pxp, Serpna3n).

Pathways with substantially higher expression in the malarial brain were chromatin remodeling genes (Htaitip, Nptxs, Mbd3, H2cfx, Hist \1h2b, Myst3, Nap1l3), cell development, chiefly genes related to negative regulation of apoptosis (Pten, Rblcc1, Stat5b, Eefk2, Polb, Nsh2), lipid metabolism (Adipor1, Fads2, Lysla1, Psap, Scd2), hydrolase activity (specifically, notrophenylphospatase), magnesium ion binding (Arsa, Atp1a1, Atp2a2, Brsk1, Cno16l), adult walking behavior (Cacnb4, Glrb), axon (Alcam, Dpysl2, Pacb1), and regulation of muscle contraction (Atp2a2, Atp1a1). Interestingly, both neuronal and vascular endothelial cell apoptosis have been described in human and experimental cerebral malaria, in association with glial cell damage and dysfunction [22,29,36] demonstrating that protein regulation occurs both at the transcription and the translation levels. The finding that substantial numbers of genes involved in chromatin remodeling are regulated in the infected brain raises the possibility that, in addition to involvement of epigenetic factors in the parasite itself [30], a major consequence of infection may be the epigenetic reprogramming of host nervous tissue.

These analyses of pathways affected by infection revealed that genes expected to be important in cerebral function (receptors cytokines, apoptosis, lipid metabolism, walking, axon, and muscle contraction) were disproportionately affected in these brains. As an additional method to mine the data corresponding to gene alteration in the brains of infected mice, we determined whether genes whose expression was altered were known to be associated with human neurological disease.

As can be seen from Table 2, the major subcategories of genes linked to neurological diseases that are up- and downregulated in malaria brain are channels/ receptors/transporters and components of the synapse including cytoskeletal linkages to vesicles. Channel genes with altered expression include Glrb (the beta subunit of the glycine receptor), Scn1b (the beta subunit of the voltage gated sodium channel), Cacnb4 (a beta subunit of voltage-dependent calcium channel), Cabp1 (a neuronspecific regulator of calcium channel activation), Accn2 (the neuronal amiloride sensitive cation channel2), Slc33a1 (the acetyl co-A transporter involved in gangliosides), and Vdac3 (the mitochondrial voltage-dependent anion channel). Genes whose encoded proteins are involved in synaptic or other contact between cells include Adam23 (which mediates integrin cell adhesion in brain), Ap2a1 (calcium Huntington interacting protein that links clathrin to receptors in vesicles [34], Akap8l and Akap9 (the latter of which also known as Yotaio, anchor protein kinase A and binds the Nr1 subunit to the cytoskeleton to the vesicle fusion protein Snap29 [23]), Scrib (a presynaptic scaffolding molecule), Pcdha6 and Pcdh9 (proto cadherins that link neural cells), Nlgn3 (neuroligin3, a neuron cell surface protein involved in formation of remodeling of CNS synapses), Nrnx2 (neurexin2, a neuron cell surface protein required for normal transmitter release), Rims3 (which enhances neurotransmitter release [21]), Cntnab1 (a contactin associated protein important for neurite outgrowth and differentiation), Gabarap (which links the Gabaa receptor with cytoskeleton), Gripap1 (a neuron-specific guanine release factor associated with the AMPA complex), Itsn1 (intersection 1, which associates with Ehb2 tyrosine kinase and the cytoskeletal protein Wasp to mediate dendritic spine morphogenesis). Several mitochondrial genes are regulated in the malaria brain whose dysfunction is associated with neurological disorders [7], including Vdac3 as mentioned above, Tmem70, Sncoa2, and Acad8.

GB Acc NAME SYMBOL I/C P-I/C Neurological  consequence  of ablation/mutation
A. Channels receptors transporters and synapse components
NM 010298 glycine receptor, beta subunit Glrb 1.9 0.023 Hyperekplexia, autosomal recessive
NM 011322 sodium channel, voltage-gated, type I, beta Scn1b 2.0 0.018 Generalized  epilepsy  with  febrile  seizures; regulates Na channel density and localization
NM 146123 calcium  channel,  voltage-dependent, beta 4 subunit Cacnb4 2.2 0.033 Mouse  “lethargic”:  ataxic,  first  example  of neurological disease in accessory subunit
NM 013879 calcium binding protein 1 Cabp1 2.5 0.048 Neuronal signal transduction and memory
NM 009597 amiloride-sensitive cation channel 2, neuronal Accn2 1.8 0.032 Enhanced fear conditioning; deletion protective in EAE
NM 015728 solute  carrier  family  33  (acetyl-coa transporter), member 1 Slc33a1 1.8 0.004 Spastic paraplegia42, autsomal dominant
NM 011696 voltage-dependent anion channel 3 Vdac3 1.5 0.017 Mitochondrial disease
XM 344168 vesicle-associated membrane protein 4 (predicted) Vamp4 2.3 0.009 Vesicle component
B. Genes involved in synapse or other inter-cellular contact
NM 017476 A kinase (PRKA) anchor protein 8-like Akap8l 3.4 0.042 Binds huntingtin in Huntington disease
NM 007458 Adaptor protein complex AP-2, alpha 1 subunit Ap2a1 2.1 0.016 Huntingtin protein binding; vesicle trafficking
NM 194462 A  kinase  (PRKA)  anchor  protein (yotiao) 9 Akap9 2.1 0.011 Long QT syndrome 11 [kcnq1, ser1570leu]
NM 011780 A  disintegrin  and  metalloprotease domain 23 Adam23 2.0 0.012 Brain specific
NM 023348 Synaptosomal-associated protein Snap29 1.8 0.015 Cerebral  dysgenesis,  neuropathy,  ichthyosis, and palmoplantar keratoderma syndrome
NM 134089 Scribbled homolog (Drosophila) Scrib 1.7 0.045 Craniorachischisis, a severe neural tube defect
XM 139187 Protocadherin 9 Pcdh9 2.2 0.015 Possibly autism
NM 172932 Neuroligin 3 Nlgn3 2.3 0.041 Ligand for neurexin: linked to autism, Asperger syndrome
NM 007767 Protocadherin alpha 6 Pcdha6 2.1 0.024 Synaptic junction protein
NM 020253 Neurexin II Nrxn2 2.4 0.001 Organize presynaptic terminals by functionally coupling Ca channels to presynaptic machinery
NM 153508 Calsyntenin 3 Clstn3 2.8 0.006 Postsynaptic protein
NM 016782 Contactin associated protein 1 Cntnap1 2.9 0.010 Essential for formation of axonal septate junc-tions
NM 182929 Regulating synaptic membrane exocy-tosis 3 Rims3 2.3 0.005 Enhances neurotransmitter secretion
NM 019749 Gamma-aminobutyric  acid  receptor-associated protein Gabarap 1.9 0.030 Autophagy; binding GABA-A receptors
NM 207670 GRIP1-associated protein 1 Gripap1 1.8 0.038 Regulates  neuronal  Ras  signaling  and  con-tributes to the regulation of AMPA receptor distribution
NM 010587 Intersectin 1 (SH3 domain protein 1A) Itsn1 2.0 0.029 Dendritic spine morphogenesis
B. Genes involved in synapse or other inter-cellular contact
C. Mitochondrial genes associated with neurological disorders
AK181541 Transmembrane protein 70 Tmem70 2.1 0.038 Encephalomyopathy and mitochondrial DNA depletion syndrome
NM 025862 Acyl-Coenzyme   A   dehydrogenase family, member 8 Acad8 1.8 0.031 Isobutyryl-coa dehydrogenase deficiency
NM 011506 Succinate-Coenzyme A ligase, ADP-forming, beta subunit Sucla2 2.7 0.032 Encephalomyopathy and mitochondrial DNA depletion syndrome
GB Acc NAME SYMBOL I/C P-I/C Neurological consequence  of ablation/mutation
D. Ataxia and cerebellar function and development
NM 145358 Calcium/calmodulin-dependent protein kinase kinase 2, beta Camkk2 3.1 0.003 Mouse null impaired spatial memory for-mation;  altered  cerebellar  granule  cell development
NM 021477 Ataxin 2 binding protein 1, transcript variant 2 A2bp1 2.7 0.045 Spinocerebellar ataxia 2
NM 033526 Ubiquilin 4 Ubqln4 2.7 0.009 Spinocerebellar ataxia 1
NM 007597 Calnexin Canx 2.6 0.019 Unstable  gait,  truncal  ataxia,  abnormal relexes; loss of large nerve fibers
NM 011179 Prosaposin Psap 1.9 0.047 Loss of cerebellar purkinje cells due to ceremide buildup
D26114 CCG1, complete cds CCG1, complete cds 1.6 0.029 Neuropathy ataxia-17syndrome;  spinocerebellar
E. Genes associated with autism
NM 011814 Fragile X mental retardation gene 2, autosomal homolog Fxr2h 2.0 0.028 Mental retardation
NM 054097 Phosphatidylinositol-4-phosphate   5-kinase, type II, gamma Pip5k2c 1.9 0.025 Mental retardation
F. Genes associated with Alzheimer’s disease
NM 009685 Amyloid beta (A4) precursor protein-binding, family B, member 1 Apbb1 1.6 0.031 Dementia of the Alzheimer’s type
G. Other
NM 009053 Radical fringe gene homolog (Drosophila) Rfng 2.0 0.022 Notch signaling in cell fate determination in neurogenesis
NM 010487 ELAV  (embryonic  lethal,  abnormal  vision, Drosophila)-like 3 (Hu antigen C) Elavl3 1.8 0.018 Paraneoplastic neurologic disorder due to autoimmune neuronal destruction

Table 2: Neurological diseases corresponding to genes altered in malarial brain.

Our study of transcriptomic regulation in the setting of cerebral malaria identified numerous genes whose altered expression or mutation has been associated with disorders of brain. Many of these regulated genes are associated with ataxia or altered cerebellum development or function (e.g.: Camkk2, A2bp1, Ubqln4, Canx, Cacnb4, Psap, CCG1), consistent with a common neurological consequence of the disease [32]. It is also noteworthy that several of the encoded proteins (Fxr2h, Pip5k2c, Pcdh9) have been associated with autism [27], which in a small study of 20 children in Tanzania was diagnosed in a significant fraction of CM patients [26]. Another neurological overlap is with Alzheimer’s disease. Delahaye et al. [9] reported overexpression of beta amyloid only in a mouse strain susceptible to cerebral malaria. In addition, axonal damage has been demonstrated as a feature of cerebral malaria with increased immunoreactivity of the amyloid precursor protein (APP) in the white matter adjacent to areas of vascular damage and of hemorrhage [28]. In Table 2, we demonstrate that Apbb1 mRNA is significantly upregulated in infected brain.


The classification of cerebral malaria as a vascular disease [5,11] emphasizes the therapeutic potential of agents directed toward increasing brain perfusion. Long-term cognitive and motor deficits correspond with the geographical distribution of vascular damage in experimental cerebral malaria [8]. Likewise, decreased cerebral blood flow has been demonstrated to contribute to mortality in cerebral malaria, and vasodilitory agents increase survival in the experimental model [5]. However, focusing exclusively on microvascular damage presents an incomplete approach to a complex disease process, as cerebral malaria is also unquestionably a disease that affects neural components of the brain, resulting in impaired gait, cognition and neural processing, as well as cognitive and motor impairment [8, 10]. The identification of altered genes encoding proteins within pathways prominently associated with neurologic disease in the present study provides alternative or adjunctive disease targets to improve treatment outcomes for the vast number of individuals who have recovered from acute parasitic infection but for whom there is neural damage that extends beyond impaired brain microcirculation.


This work was supported by the NIH Training Grant in Mechanisms of Cardiovascular Diseases (T32 HL-07675) to MSD; Dominick P. Purpura Department of Neuroscience and Department of Psychiatry and Behavioral Sciences (neuroscience fellowship support to MSD), Albert Einstein College of Medicine; Burroughs-Wellcome Fund’s Career Awards for Medical Scientists to MSD; Einstein-Montefiore Institute for Clinical and Translational Research Career Development Award to MSD; AI076248 to HBT; AI39454 to LMW; NS041282 to DCS.


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