Reversal of neurological deficits by painless nerve growth factor in a mouse model of Rett syndrome.

Rett syndrome is a rare genetic neurodevelopmental disease, affecting 1 in over 10 000 females born worldwide, caused by de novo mutations in the X-chromosome-located methyl-CpG-binding protein 2 (MeCP2) gene. Despite the great effort put forth by the scientific community, a therapy for this devastating disease is still needed. Here, we tested the therapeutic effects of a painless mutein of the nerve growth factor (NGF), called human NGF painless (hNGFp), via a non-invasive intranasal delivery in female MeCP2+/- mice. Of note, previous work had demonstrated a broad biodistribution of hNGFp in the mouse brain by the nasal delivery route. We report that (i) the long-term lifelong treatment of MeCP2+/- mice with hNGFp, starting at 2 months of age, increased the chance of survival while also greatly improving behavioural parameters. Furthermore, when we assessed the phenotypic changes brought forth by (ii) a short-term 1-month-long hNGFp-treatment, starting at 3 months of age (right after the initial presentation of symptoms), we observed the rescue of a well known neuronal target population of NGF, cholinergic neurons in the medial septum. Moreover, we reveal a deficit in microglial morphology in MeCP2+/- mice, completely reversed in treated animals. This effect on microglia is in line with reports showing microglia to be a TrkA-dependent non-neuronal target cell population of NGF in the brain. To understand the immunomodulatory activity of hNGFp, we analysed the cytokine profile after hNGFp treatment in MeCP2+/- mice, to discover that the treatment recovered the altered expression of key neuroimmune-communication molecules, such as fractalkine. The overall conclusion is that hNGFp delivered intranasally can ameliorate symptoms in the MeCP2+/- model of Rett syndrome, by exerting strong neuroprotection with a dual mechanism of action: directly on target neurons and indirectly via microglia.

A comprehensive atlas of perineuronal net distribution and colocalization with parvalbumin in the adult mouse brain.

Perineuronal nets (PNNs) surround specific neurons in the brain and are involved in various forms of plasticity and clinical conditions. However, our understanding of the PNN role in these phenomena is limited by the lack of highly quantitative maps of PNN distribution and association with specific cell types. Here, we present a comprehensive atlas of Wisteria floribunda agglutinin (WFA)-positive PNNs and colocalization with parvalbumin (PV) cells for over 600 regions of the adult mouse brain. Data analysis shows that PV expression is a good predictor of PNN aggregation. In the cortex, PNNs are dramatically enriched in layer 4 of all primary sensory areas in correlation with thalamocortical input density, and their distribution mirrors intracortical connectivity patterns. Gene expression analysis identifies many PNN-correlated genes. Strikingly, PNN-anticorrelated transcripts are enriched in synaptic plasticity genes, generalizing PNNs' role as circuit stability factors.

Selective Disruption of Perineuronal Nets in Mice Lacking Crtl1 is Sufficient to Make Fear Memories Susceptible to Erasure.

The ability to store, retrieve, and extinguish memories of adverse experiences is an essential skill for animals' survival. The cellular and molecular factors that underlie such processes are only partially known. Using chondroitinase ABC treatment targeting chondroitin sulfate proteoglycans (CSPGs), previous studies showed that the maturation of the extracellular matrix makes fear memory resistant to deletion. Mice lacking the cartilage link protein Crtl1 (Crtl1-KO mice) display normal CSPG levels but impaired CSPG condensation in perineuronal nets (PNNs). Thus, we asked whether the presence of PNNs in the adult brain is responsible for the appearance of persistent fear memories by investigating fear extinction in Crtl1-KO mice. We found that mutant mice displayed fear memory erasure after an extinction protocol as revealed by analysis of freezing and pupil dynamics. Fear memory erasure did not depend on passive loss of retention; moreover, we demonstrated that, after extinction training, conditioned Crtl1-KO mice display no neural activation in the amygdala (Zif268 staining) in comparison to control animals. Taken together, our findings suggest that the aggregation of CSPGs into PNNs regulates the boundaries of the critical period for fear extinction.

Behavioral impulsivity is associated with pupillary alterations and hyperactivity in CDKL5 mutant mice.

Cyclin-dependent kinase-like 5 (Cdkl5) deficiency disorder (CDD) is a severe neurodevelopmental condition caused by mutations in the X-linked Cdkl5 gene. CDD is characterized by early-onset seizures in the first month of life, intellectual disability, motor and social impairment. No effective treatment is currently available and medical management is only symptomatic and supportive. Recently, mouse models of Cdkl5 disorder have demonstrated that mice lacking Cdkl5 exhibit autism-like phenotypes, hyperactivity and dysregulations of the arousal system, suggesting the possibility to use these features as translational biomarkers. In this study, we tested Cdkl5 male and female mutant mice in an appetitive operant conditioning chamber to assess cognitive and motor abilities, and performed pupillometry to assess the integrity of the arousal system. Then, we evaluated the performance of artificial intelligence models to classify the genotype of the animals from the behavioral and physiological phenotype. The behavioral results show that CDD mice display impulsivity, together with low levels of cognitive flexibility and perseverative behaviors. We assessed arousal levels by simultaneously recording pupil size and locomotor activity. Pupillometry reveals in CDD mice a smaller pupil size and an impaired response to unexpected stimuli associated with hyperlocomotion, demonstrating a global defect in arousal modulation. Finally, machine learning reveals that both behavioral and pupillometry parameters can be considered good predictors of CDD. Since early diagnosis is essential to evaluate treatment outcomes and pupillary measures can be performed easily, we proposed the monitoring of pupil size as a promising biomarker for CDD.

Learning to count biological structures with raters' uncertainty.

Exploiting well-labeled training sets has led deep learning models to astonishing results for counting biological structures in microscopy images. However, dealing with weak multi-rater annotations, i.e., when multiple human raters disagree due to non-trivial patterns, remains a relatively unexplored problem. More reliable labels can be obtained by aggregating and averaging the decisions given by several raters to the same data. Still, the scale of the counting task and the limited budget for labeling prohibit this. As a result, making the most with small quantities of multi-rater data is crucial. To this end, we propose a two-stage counting strategy in a weakly labeled data scenario. First, we detect and count the biological structures; then, in the second step, we refine the predictions, increasing the correlation between the scores assigned to the samples and the raters' agreement on the annotations. We assess our methodology on a novel dataset comprising fluorescence microscopy images of mice brains containing extracellular matrix aggregates named perineuronal nets. We demonstrate that we significantly enhance counting performance, improving confidence calibration by taking advantage of the redundant information characterizing the small sets of available multi-rater data.