An alternative conformation of the N-terminal loop of human dihydroorotate dehydrogenase drives binding to a potent antiproliferative agent.

Over the years, human dihydroorotate dehydrogenase (hDHODH), which is a key player in the de novo pyrimidine-biosynthesis pathway, has been targeted in the treatment of several conditions, including autoimmune disorders and acute myelogenous leukaemia, as well as in host-targeted antiviral therapy. A molecular exploration of its inhibitor-binding behaviours yielded promising candidates for innovative drug design. A detailed description of the enzymatic pharmacophore drove the decoration of well-established inhibitory scaffolds, thus gaining further in vitro and in vivo efficacy. In the present work, using X-ray crystallography, an atypical rearrangement was identified in the binding pose of a potent inhibitor characterized by a polar pyridine-based moiety (compound 18). The crystal structure shows that upon binding compound 18 the dynamics of a protein loop involved in a gating mechanism at the cofactor-binding site is modulated by the presence of three water molecules, thus fine-tuning the polarity/hydrophobicity of the binding pocket. These solvent molecules are engaged in the formation of a hydrogen-bond mesh in which one of them establishes a direct contact with the pyridine moiety of compound 18, thus paving the way for a reappraisal of the inhibition of hDHODH. Using an integrated approach, the thermodynamics of such a modulation is described by means of isothermal titration calorimetry coupled with molecular modelling. These structural insights will guide future drug design to obtain a finer Kd/logD7.4 balance and identify membrane-permeable molecules with a drug-like profile in terms of water solubility.

Inflammatory, metabolic, and sex-dependent gene-regulatory dynamics of microglia and macrophages in neonatal hippocampus after hypoxia-ischemia.

Neonatal hypoxia-ischemia (HI) is a major cause of perinatal death and long-term disabilities worldwide. Post-ischemic neuroinflammation plays a pivotal role in HI pathophysiology. In the present study, we investigated the temporal dynamics of microglia (CX3CR1GFP/+) and infiltrating macrophages (CCR2RFP/+) in the hippocampi of mice subjected to HI at postnatal day 9. Using inflammatory pathway and transcription factor (TF) analyses, we identified a distinct post-ischemic response in CCR2RFP/+ cells characterized by differential gene expression in sensome, homeostatic, matrisome, lipid metabolic, and inflammatory molecular signatures. Three days after injury, transcriptomic signatures of CX3CR1GFP/+ and CCR2RFP/+ cells isolated from hippocampi showed a partial convergence. Interestingly, microglia-specific genes in CX3CR1GFP/+ cells showed a sexual dimorphism, where expression returned to control levels in males but not in females during the experimental time frame. These results highlight the importance of further investigations on metabolic rewiring to pave the way for future interventions in asphyxiated neonates.

Brain Maturation as a Fundamental Factor in Immune-Neurovascular Interactions in Stroke.

Injuries in the developing brain cause significant long-term neurological deficits. Emerging clinical and preclinical data have demonstrated that the pathophysiology of neonatal and childhood stroke share similar mechanisms that regulate brain damage, but also have distinct molecular signatures and cellular pathways. The focus of this review is on two different diseases-neonatal and childhood stroke-with emphasis on similarities and distinctions identified thus far in rodent models of these diseases. This includes the susceptibility of distinct cell types to brain injury with particular emphasis on the role of resident and peripheral immune populations in modulating stroke outcome. Furthermore, we discuss some of the most recent and relevant findings in relation to the immune-neurovascular crosstalk and how the influence of inflammatory mediators is dependent on specific brain maturation stages. Finally, we comment on the current state of treatments geared toward inducing neuroprotection and promoting brain repair after injury and highlight that future prophylactic and therapeutic strategies for stroke should be age-specific and consider gender differences in order to achieve optimal translational success.

AI-powered assessment of biomarkers for growth prediction of abdominal aortic aneurysms.

Objective: The purpose of this study was to employ biomechanics-based biomarkers to locally characterize abdominal aortic aneurysm (AAA) tissue and investigate their relation to local aortic growth by means of an artificial intelligence model. Methods: The study focused on a population of 36 patients with AAAs undergoing serial monitoring with electrocardiogram-gated multiphase computed tomography angiography acquisitions. The geometries of the aortic lumen and wall were reconstructed from the baseline scans and used for the baseline assessment of regional aortic weakness with three functional biomarkers, time-averaged wall-shear stress, in vivo principal strain, and intra-luminal thrombus thickness. The biomarkers were encoded as regional averages on axial and circumferential sections perpendicularly to the aortic centerline. Local diametric growth was obtained as difference in diameter between baseline and follow-up at the level of each axial section. An artificial intelligence model was developed to predict accelerated aneurysmal growth with the Extra Trees algorithm used as a binary classifier where the positive class represented regions that grew more than 2.5 mm/year. Additional clinical biomarkers, such as maximum aortic diameter at baseline, were also investigated as predictors of growth. Results: The area under the curve for the constructed receiver operating characteristic curve for the Extra Trees classifier showed a very good performance in predicting relevant aortic growth (area under the curve = 0.92), with the three biomechanics-based functional biomarkers being objectively selected as the main predictors of growth. Conclusions: The use of features based on the functional and local characterization of the aortic tissue resulted in a superior performance in terms of growth prediction when compared with models based on geometrical assessments. With rapid growth linked to increasing risk for patients with AAAs, the ability to access functional information related to tissue weakening and disease progression at baseline has the potential to support early clinical decisions and improve disease management.

A classification approach to improve out of sample predictability of structure-based constitutive models for ascending thoracic aortic tissue.

In this research, a pipeline was developed to assess the out-of-sample predictive capability of structure-based constitutive models of ascending aortic aneurysmal tissue. The hypothesis being tested is that a biomarker can help establish similarities among tissues sharing the same level of a quantifiable property, thus enabling the development of biomarker-specific constitutive models. Biomarker-specific averaged material models were constructed from biaxial mechanical tests of specimens that shared similar biomarker properties such as level of blood-wall shear stress or microfiber (elastin or collagen) degradation in the extracellular matrix. Using a cross-validation strategy commonly used in classification algorithms, biomarker-specific averaged material models were assessed in contrast to individual tissue mechanics of out of sample specimens that fell under the same category but did not contribute to the averaged model's generation. The normalized root means square errors (NRMSE) calculated on out-of-sample data were compared with average models when no categorization was performed versus biomarker-specific models and among different level of a biomarker. Different biomarker levels exhibited statistically different NRMSE when compared among each other, indicating more common features shared by the specimens belonging to the lower error groups. However, no specific biomarkers reached a significant difference when compared to the average model created when No Categorization was performed, possibly on account of unbalanced number of specimens. The method developed could allow for the screening of different biomarkers or combinations/interactions in a systematic manner leading the way to larger datasets and to more individualized constitutive approaches.

Magnetic resonance imaging-based hemodynamic wall shear stress alters aortic wall tissue biomechanics in bicuspid aortic valve patients.

OBJECTIVE: In this study we aimed to conclusively determine whether altered aortic biomechanics are associated with wall shear stress (WSS) independent of region of tissue collection. Elevated WSS in the ascending aorta of patients with bicuspid aortic valve has been shown to contribute to local maladaptive aortic remodeling and might alter biomechanics. METHODS: Preoperative 4-dimensional flow magnetic resonance imaging was performed on 22 patients who underwent prophylactic aortic root and/or ascending aorta replacement. Localized elevated WSS was identified in patients using age-matched healthy atlases (n = 60 controls). Tissue samples (n = 78) were collected and categorized according to WSS (elevated vs normal) and region. Samples were subjected to planar biaxial testing. To fully quantify the nonlinear biomechanical response, the tangential modulus (local stiffness) at a low-stretch (LTM) and high-stretch (HTM) linear region and the onset (TZo) and end stress of the nonlinear transition zone were measured. A linear mixed effect models was implemented to determine statistical relationships. RESULTS: A higher LTM in the circumferential and axial direction was associated with elevated WSS (P = .007 and P = .018 respectively) independent of collection region. Circumferential TZo and HTM were higher with elevated WSS (P = .024 and P = .003); whereas the collection region was associated with variations in axial TZo (P = .013), circumferential HTM (P = .015), and axial HTM (P = .001). CONCLUSIONS: This study shows strong evidence that biomechanical changes in the aorta are strongly associated with hemodynamics, and not region of tissue collection for bicuspid valve aortopathy patients. Elevated WSS is associated with tissue behavior at low stretch ranges (ie, LTM and TZo).

Elastin integrity in bicuspid valve-associated aortopathy is associated with altered biomechanical properties and influenced by age.

Background: Aortic wall remodelling in bicuspid aortic valve (BAV) patients is heterogeneous and characterized by elastin fiber breakdown alongside impaired biomechanics. However, the relationship between aortic histopathological changes and biomechanics are incompletely understood. We clarify the influence of elastin fiber integrity on ex vivo aortic wall mechanical properties in BAV patients, and explore the influence of patient age. Methods: Aortic tissue samples (N=66) from 19 BAV patients undergoing prophylactic ascending aortic resection surgery were analyzed. Semi-quantitative histopathological analysis was conducted to assess elastin fiber integrity including elastin content and elastic fiber fragmentation. Ex vivo biaxial mechanical testing generated stress-strain curves from which physiological [low-strain tangential modulus (LTM), transition zone onset stress (TZo)] and supraphysiological [transition zone end stress (TZe) and high-strain tangential modulus (HTM)] mechanical properties were obtained. Relationships between histopathology and mechanical properties were determined using a linear mixed effect model. BAV patients were subdivided according to 'younger' and 'older' age groups (i.e., 51-60 and 61-70 years old, respectively). Results: No statistically significant differences in elastin content were observed between younger and older BAV patients. Older patients showed greater elastin fiber fragmentation compared to their younger cohort (74% versus 61%). Elastin fiber histopathology was associated with differences in physiological mechanical properties: elastin fragmentation corresponded with lower LTM (P=0.005) and TZo (P=0.044) in younger BAV patients and higher LTM (P=0.049) and TZo (P=0.001) in older BAV patients. Histopathology changes were significantly associated with supraphysiological mechanical properties only in older BAV patients: decreased elastin integrity was associated with increased TZe (P=0.049) and HTM (P<0.001). Conclusions: Elastin histopathologic changes in BAV aortopathy correspond with differences in mechanical properties and this relationship is influenced by patient age. These novel findings provide additional mechanistic insights into aortic wall remodeling and support a more nuanced stratification of BAV patients by age.

Clinical implications of the biomechanics of bicuspid aortic valve and bicuspid aortopathy.

Bicuspid aortic valve (BAV), which affects up to 2% of the general population, results from the abnormal fusion of the cusps of the aortic valve. Patients with BAV are at a higher risk for developing aortic dilatation, a condition known as bicuspid aortopathy, which is associated with potentially life-threatening sequelae such as aortic dissection and aortic rupture. Although BAV biomechanics have been shown to contribute to aortopathy, their precise impact is yet to be delineated. Herein, we present the latest literature related to BAV biomechanics. We present the most recent definitions and classifications for BAV. We also summarize the current evidence pertaining to the mechanisms that drive bicuspid aortopathy. We highlight how aberrant flow patterns can contribute to the development of aortic dilatation. Finally, we discuss the role cardiac magnetic resonance imaging can have in assessing and managing patient with BAV and bicuspid aortopathy.

Biomechanics in ascending aortic aneurysms correlate with tissue composition and strength.

Objective: This study correlates low strain tangential modulus (LTM) and transition zone onset (TZo) stress, biomechanical parameters that occur within the physiological range of stress seen in vivo, with tissue strength and histopathologic changes in aneurysmal ascending aortic tissue. Method: Ascending aortic aneurysm tissue samples were collected from 41 patients undergoing elective resection. Samples were subjected to planar biaxial testing to quantify LTM and TZo. These were then correlated with strength assessed from uniaxial testing and with histopathologic quantification of pathologic derangements in elastin, collagen, and proteoglycan (PG). Results: Decreased LTM and TZo were correlated with reduced strength (P < .05), PG content (P < .05), and elastin content (P < .05). Reduced TZo also was correlated with increased elastin fragmentation (P < .05). Conclusions: LTM and TZo are correlated with common biomechanical and histopathologic alterations in ascending aortic aneurysm tissue that are thought to relate to the risk of acute aortic syndromes. LTM and TZo are measured under conditions approximating in vivo physiology and have the potential to be obtained noninvasively using medical imaging techniques. Therefore, they represent parameters that warrant future study as potential contributors to our growing knowledge of pathophysiology, disease progression, and risk stratification of aortic disease.

Metabarcoding of fungal assemblages in Vaccinium myrtillus endosphere suggests colonization of above-ground organs by some ericoid mycorrhizal and DSE fungi.

Plants harbor in their external surfaces and internal tissues a highly diverse and finely structured microbial assembly, the microbiota. Each plant compartment usually represents a unique ecological niche hosting a distinct microbial community and niche differentiation, which may mirror distinct functions of a specialized microbiota, has been mainly investigated for bacteria. Far less is known for the fungal components of the plant-associated microbiota. Here, we applied a metabarcoding approach to describe the fungal assemblages in different organs of Vaccinium myrtillus plants (Ericaceae) collected in a subalpine meadow in North-West Italy, and identified specific taxa enriched in internal tissues of roots, stems, leaves and flowers. We also traced the distribution of some important fungi commonly associated with plants of the family Ericaceae, namely the ericoid mycorrhizal (ErM) fungi and the dark septate endophytes (DSE), both playing important roles in plant growth and health. Operational taxonomic units attributed to established ErM fungal species in the genus Hyaloscypha and to DSE species in the Phialocephala-Acephala applanata complex (PAC) were found in all the plant organs. Mycorrhizal fungi are thought to be strictly associated with the plant roots, and this first observation of ErM fungi in the above-ground organs of the host plant may be explained by the evolutionary closeness of ErM fungi in the genus Hyaloscypha with non mycorrhizal fungal endophytes. This is also witnessed by the closer similarities of the ErM fungal genomes with the genomes of plant endophytes than with those of other mycorrhizal fungi, such as arbuscular or ectomycorrhizal fungi.

Deep-learning method for fully automatic segmentation of the abdominal aortic aneurysm from computed tomography imaging.

Abdominal aortic aneurysm (AAA) is one of the leading causes of death worldwide. AAAs often remain asymptomatic until they are either close to rupturing or they cause pressure to the spine and/or other organs. Fast progression has been linked to future clinical outcomes. Therefore, a reliable and efficient system to quantify geometric properties and growth will enable better clinical prognoses for aneurysms. Different imaging systems can be used to locate and characterize an aneurysm; computed tomography (CT) is the modality of choice in many clinical centers to monitor later stages of the disease and plan surgical treatment. The lack of accurate and automated techniques to segment the outer wall and lumen of the aneurysm results in either simplified measurements that focus on few salient features or time-consuming segmentation affected by high inter- and intra-operator variability. To overcome these limitations, we propose a model for segmenting AAA tissues automatically by using a trained deep learning-based approach. The model is composed of three different steps starting with the extraction of the aorta and iliac arteries followed by the detection of the lumen and other AAA tissues. The results of the automated segmentation demonstrate very good agreement when compared to manual segmentation performed by an expert.

Biomechanical properties of ascending aortic aneurysms: Quantification of inter- and intra-patient variability.

This study investigates the biomechanical properties of ascending aortic aneurysms focusing on the inter-patient differences vs. the heterogeneity within a patient's aneurysm. Each specimen was tested on a biaxial testing device and the resulting stress-strain response was fitted to a four-parameter Fung constitutive model. We postulate that the inter-patient variability (differences between patients) blurs possible intra-patient variability (regional heterogeneity) and, thus, that both effects must be considered to shed light on the role of heterogeneity in aneurysm progression. We propose, demonstrate, and discuss two techniques to assess differences by, first, comparing conventional biomechanical properties and, second, the overall constitutive response. Results show that both inter- and intra-patient variability contribute to errors when using population averaged models to fit individual tissue behaviour. When inter-patient variability was accounted for and its effects excluded, intra-patient heterogeneity could be assessed, showing a wide degree of heterogeneity at the individual patient level. Furthermore, the right lateral region (from the patient's perspective) appeared different (stiffer) than the other regions. We posit that this heterogeneity could be a consequence of maladaptive remodelling due to altered loading conditions that hastens microstructural changes naturally occurring with age. Further validation of these results should be sought from a larger cohort study.

Umbilical cord-derived mesenchymal stromal cells immunomodulate and restore actin dynamics and phagocytosis of LPS-activated microglia via PI3K/Akt/Rho GTPase pathway.

Microglia are the immune cells in the central nervous system surveying environment and reacting to various injuries. Activated microglia may cause impaired synaptic plasticity, therefore modulating and restoring them to neutral phenotype is crucial to counteract a pro-inflammatory, neurotoxic state. In this study, we focused on elucidating whether human umbilical cord (UC) -derived mesenchymal stromal cells (MSCs) can exert immunomodulatory effect and change the phenotype of activated microglia. Primary culture of microglia was activated by lipopolysaccharide (LPS) and was co-cultured with three lots of MSCs. We investigated immunomodulation, actin dynamics and phagocytic capacity of activated microglia, and examined change of Rho GTPase in microglia as the mechanism. MSCs suppressed the expression of IL-1ß and pNFκB in LPS-activated microglia, and conversely elevated the expression of IL-1ß in resting-surveying microglia with lot-to-lot variation. Morphological and phagocytotic analyses revealed that LPS stimulation significantly increased active Rho GTPase, Rac1, and Cdc42 levels in the microglia, and their morphology changed to amoeboid in which F-actin spread with ruffle formation. The F-actin spreading persisted after removal of LPS stimulation and reduced phagocytosis. On the other hand, MSC co-culture induced bimodal increase in active Rac1 and Cdc42 levels in LPS-activated microglia. Moreover, extended ruffles of F-actin shrinked and concentrated to form an actin ring, thereby restoring phagocytosis. We confirmed inhibition of the PI3K/Akt pathway attenuated F-actin dynamics and phagocytosis restored by MSCs. Overall, we demonstrated that MSCs immunomodulated microglia with lot-to-lot variation, and changed the phenotype of LPS-activated microglia restoring actin dynamics and phagocytosis by increase of active Rho GTPase.

Linking Aortic Mechanical Properties, Gene Expression and Microstructure: A New Perspective on Regional Weakening in Abdominal Aortic Aneurysms.

Background: Current clinical practice for the assessment of abdominal aortic aneurysms (AAA) is based on vessel diameter and does not account for the multifactorial, heterogeneous remodeling that results in the regional weakening of the aortic wall leading to aortic growth and rupture. The present study was conducted to determine correlations between a novel non-invasive surrogate measure of regional aortic weakening and the results from invasive analyses performed on corresponding ex vivo aortic samples. Tissue samples were evaluated to classify local wall weakening and the likelihood of further degeneration based on non-invasive indices. Methods: A combined, image-based fluid dynamic and in-vivo strain analysis approach was used to estimate the Regional Aortic Weakness (RAW) index and assess individual aortas of AAA patients prior to elective surgery. Nine patients were treated with complete aortic resection allowing the systematic collection of tissue samples that were used to determine regional aortic mechanics, microstructure and gene expression by means of mechanical testing, microscopy and transcriptomic analyses. Results: The RAW index was significantly higher for samples exhibiting lower mechanical strength (p = 0.035) and samples classified as low elastin content (p = 0.020). Samples with higher RAW index had the greatest number of genes differentially expressed compared to any constitutive metric. High RAW samples showed a decrease in gene expression for elastin and a down-regulation of pathways responsible for cell movement, reorganization of cytoskeleton, and angiogenesis. Conclusions: This work describes the first AAA index free of assumptions for material properties and accounting for patient-specific mechanical behavior in relation to aneurysm strength. Use of the RAW index captured biomechanical changes linked to the weakening of the aorta and revealed changes in microstructure and gene expression. This approach has the potential to provide an improved tool to aid clinical decision-making in the management of aortic pathology.

Frequency of the two mating types in the soil under productive and non-productive trees in five French orchards of the Périgord black truffle (Tuber melanosporum Vittad.).

The Périgord black truffle (Tuber melanosporum Vittad.) is an ectomycorrhizal fungus forming edible fructifications. The production of T. melanosporum relies mainly on man-made plantations. T. melanosporum is a heterothallic species requiring the meeting of two partners of opposite mating types to fruit. It is common to have productive and non-productive trees in the same orchard. The aim of our study was to assess the distribution of T. melanosporum mating types in soil under productive and non-productive trees to test whether the presence or absence of one or two mating types could be an indicator of productivity. To achieve this aim, five orchards were selected in various French regions. Soils were harvested under productive and non-productive Quercus pubescens; soil characteristics and the distribution of the mating types in the soil were investigated. No significant differences between productive and non-productive soils according to soil parameters were detected. The total content of T. melanosporum DNA in the soil was significantly higher under productive trees compared with non-productive trees, and it was positively correlated only with soil available phosphorous. Under productive trees, it was more frequent to find both mating types than under non-productive trees. Soils with only one mating type were more frequent under non-productive trees than under productive ones. Moreover, no mating type was detected in the soil of 22% of the non-productive trees. These results suggest that the detection of T. melanosporum mating types in soil could be a tool to optimise the management of truffle orchards (e.g. by spore inoculation).

Biomechanics of Wound Healing in an Equine Limb Model: Effect of Location and Treatment with a Peptide-Modified Collagen-Chitosan Hydrogel.

The equine distal limb wound healing model, characterized by delayed re-epithelialization and a fibroproliferative response to wounding similar to that observed in humans, is a valuable tool for the study of biomaterials poised for translation into both the veterinary and human medical markets. In the current study, we developed a novel method of biaxial biomechanical testing to assess the functional outcomes of healed wounds in a modified equine model and discovered significant functional and structural differences in both unwounded and injured skin at different locations on the distal limb that must be considered when using this model in future work. Namely, the medial skin was thicker and displayed earlier collagen engagement, medial wounds experienced a greater proportion of wound contraction during closure, and proximal wounds produced significantly more exuberant granulation tissue. Using this new knowledge of the equine model of aberrant wound healing, we then investigated the effect of a peptide-modified collagen-chitosan hydrogel on wound healing. Here, we found that a single treatment with the QHREDGS (glutamine-histidine-arginine-glutamic acid-aspartic acid-glycine-serine) peptide-modified hydrogel (Q-peptide hydrogel) resulted in a higher rate of wound closure and was able to modulate the biomechanical function toward a more compliant healed tissue without observable negative effects. Thus, we conclude that the use of a Q-peptide hydrogel provides a safe and effective means of improving the rate and quality of wound healing in a large animal model.

Multidimensional Analysis of Descending Aortic Growth After Acute Type A Aortic Dissection.

BACKGROUND: After repair of acute type A aortic dissection, typical geometric variables of conventional aortic surveillance focus on maximum diameter and its rate of growth, potentially missing important geometric changes elsewhere. We determined additional information provided by a semiautomated, 3-dimensional (3D), nonlinear growth model of the descending thoracic aorta after repair of type A aortic dissection. METHODS: Computed tomographic angiography data were retrospectively collected after hemiarch repair of type A aortic dissection. The descending aorta was systematically reconstructed to generate a 3D model made up of individual segments. The baseline and follow-up diameters were measured semiautomatically for each segment, and the nonlinear interval growth was determined. RESULTS: The fastest growing segment expanded at a rate of 3.8 mm/y (interquartile range, 2.2 to 5.4 mm/y) vs 0.6 mm/y (interquartile range, -0.3 to 1.7 mm/y) when measured at the original site of maximum diameter (P < .01). The maximum baseline diameter was a poor predictor of location with fastest growth (r = 0.10, P > .1). Using the society recommended growth limits, a greater proportion of patients would be considered "at risk" when assessed by our method vs conventional surveillance measures. CONCLUSIONS: Our model identifies areas of rapid aortic growth after repair of type A dissection that would likely be missed using current surveillance techniques. The increased precision, resolution, and reproducibility provided by our technique may improve on limitations of current surveillance techniques, provide novel geometric data on aortic remodeling, and contribute to the pursuit of a comprehensive patient-specific approach to aortic risk stratification.

Lithium treatment reverses irradiation-induced changes in rodent neural progenitors and rescues cognition.

Cranial radiotherapy in children has detrimental effects on cognition, mood, and social competence in young cancer survivors. Treatments harnessing hippocampal neurogenesis are currently of great relevance in this context. Lithium, a well-known mood stabilizer, has both neuroprotective, pro-neurogenic as well as antitumor effects, and in the current study we introduced lithium treatment 4 weeks after irradiation. Female mice received a single 4 Gy whole-brain radiation dose on postnatal day (PND) 21 and were randomized to 0.24% Li2CO3 chow or normal chow from PND 49 to 77. Hippocampal neurogenesis was assessed on PND 77, 91, and 105. We found that lithium treatment had a pro-proliferative effect on neural progenitors, but neuronal integration occurred only after it was discontinued. Also, the treatment ameliorated deficits in spatial learning and memory retention observed in irradiated mice. Gene expression profiling and DNA methylation analysis identified two novel factors related to the observed effects, Tppp, associated with microtubule stabilization, and GAD2/65, associated with neuronal signaling. Our results show that lithium treatment reverses irradiation-induced loss of hippocampal neurogenesis and cognitive impairment even when introduced long after the injury. We propose that lithium treatment should be intermittent in order to first make neural progenitors proliferate and then, upon discontinuation, allow them to differentiate. Our findings suggest that pharmacological treatment of cognitive so-called late effects in childhood cancer survivors is possible.