In Vivo Ultrafast Doppler Imaging Combined with Confocal Microscopy and Behavioral Approaches to Gain Insight into the Central Expression of Peripheral Neuropathy in Trembler-J Mice.

The main human hereditary peripheral neuropathy (Charcot-Marie-Tooth, CMT), manifests in progressive sensory and motor deficits. Mutations in the compact myelin protein gene pmp22 cause more than 50% of all CMTs. CMT1E is a subtype of CMT1 myelinopathy carrying micro-mutations in pmp22. The Trembler-J mice have a spontaneous mutation in pmp22 identical to that present in CMT1E human patients. PMP22 is mainly (but not exclusively) expressed in Schwann cells. Some studies have found the presence of pmp22 together with some anomalies in the CNS of CMT patients. Recently, we identified the presence of higher hippocampal pmp22 expression and elevated levels of anxious behavior in TrJ/+ compared to those observed in wt. In the present paper, we delve deeper into the central expression of the neuropathy modeled in Trembler-J analyzing in vivo the cerebrovascular component by Ultrafast Doppler, exploring the vascular structure by scanning laser confocal microscopy, and analyzing the behavioral profile by anxiety and motor difficulty tests. We have found that TrJ/+ hippocampi have increased blood flow and a higher vessel volume compared with the wild type. Together with this, we found an anxiety-like profile in TrJ/+ and the motor difficulties described earlier. We demonstrate that there are specific cerebrovascular hemodynamics associated with a vascular structure and anxious behavior associated with the TrJ/+ clinical phenotype, a model of the human CMT1E disease.

c-Abl tyrosine kinase down-regulation as target for memory improvement in Alzheimer's disease.

Background: Growing evidence suggests that the non-receptor tyrosine kinase, c-Abl, plays a significant role in the pathogenesis of Alzheimer's disease (AD). Here, we analyzed the effect of c-Abl on the cognitive performance decline of APPSwe/PSEN1ΔE9 (APP/PS1) mouse model for AD. Methods: We used the conditional genetic ablation of c-Abl in the brain (c-Abl-KO) and pharmacological treatment with neurotinib, a novel allosteric c-Abl inhibitor with high brain penetrance, imbued in rodent's chow. Results: We found that APP/PS1/c-Abl-KO mice and APP/PS1 neurotinib-fed mice had improved performance in hippocampus-dependent tasks. In the object location and Barnes-maze tests, they recognized the displaced object and learned the location of the escape hole faster than APP/PS1 mice. Also, APP/PS1 neurotinib-fed mice required fewer trials to reach the learning criterion in the memory flexibility test. Accordingly, c-Abl absence and inhibition caused fewer amyloid plaques, reduced astrogliosis, and preserved neurons in the hippocampus. Discussion: Our results further validate c-Abl as a target for AD, and the neurotinib, a novel c-Abl inhibitor, as a suitable preclinical candidate for AD therapies.

Polyoxidovanadates as a pharmacological option against brain aging.

The world population is aging rapidly, and chronic diseases associated are cardiometabolic syndrome, cancer, and neurodegenerative diseases. Oxidative stress and inflammation are typical hallmarks in them. Polyoxidovanadates (POVs) have shown interesting pharmacological actions against chronic diseases. This work aimed to evaluate the POV effect on hippocampal neuroinflammation, redox balance, and recognition memory in the aging of rats. Rats 18 months old were administered a daily dose of sodium metavanadate (MV), decavanadate (DV), Metformin (Metf), or MetfDeca for two months. Results showed that short-term and long-term recognition memory improved by 28 % and 16 % (DV), 19 % and 20 % (Metf), and 21 % and 27 % (MetfDeca). In hippocampi, reactive oxygen species, IL-1ß, and TNF-α, after DV, Metf, and MetfDeca decreased at similar concentrations to young adult control, while lipid peroxidation substantially ameliorated. Additionally, superoxide dismutase and catalase activity increased by 41 % and 42 % (DV), 39 % and 41 % (Metf), and 75 % and 73 % (MetfDeca). POV treatments reduced Nrf2 and GFAP immunoreactivity in CA1 (70-87.5 %), CA3 (60-80 %), and DG (57-89 %). Metformin treatment showed a minor effect, while MV treatment did not improve any parameters. Although DV, Metf, and MetfDeca treatments showed similar results, POVs doses were 16-fold fewer than Metformin. In conclusion, DV and MetfDeca could be pharmacological options to reduce age-related neuronal damage.

Automated detection, selection and classification of hippocampal landmark points for the diagnosis of Alzheimer's disease.

BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) is a neurodegenerative, progressive, and irreversible disease that accounts for up to 80% of all dementia cases. AD predominantly affects older adults, and its clinical diagnosis is a challenging evaluation process, with imprecision rates between 12 and 23%. Structural magnetic resonance (MR) imaging has been widely used in studies related to AD because this technique provides images with excellent anatomical details and information about structural changes induced by the disease in the brain. Current studies are focused on detecting AD in its initial stage, i.e., mild cognitive impairment (MCI), since treatments for preventing or delaying the onset of symptoms is more effective when administered at the early stages of the disease. This study proposes a new technique to perform MR image classification in AD diagnosis using discriminative hippocampal point landmarks among the cognitively normal (CN), MCI, and AD populations. METHODS: Our approach, based on a two-level classification, first detects and selects discriminative landmark points from two diagnosis populations based on their matching distance compared to a probabilistic atlas of 3-D labeled landmark points. The points are classified using attributes computed in a spherical support region around each point using information from brain probability image tissues of gray matter, white matter, and cerebrospinal fluid as sources of information. Next, at the second level, the images are classified based on a quantitative evaluation obtained from the first-level classifier outputs. RESULTS: For the CN×MCI experiment, we achieved an AUC of 0.83, an accuracy of 75.58%, with 72.9% of sensitivity and 77.81% of specificity. For the MCI×AD experiment, we achieved an AUC value of 0.73, an accuracy of 69.8%, a sensitivity of 74.09% and specificity of 64.57%. Finally, for the CN×AD, we achieved an AUC of 0.95, an accuracy of 89.24%, with 85.58% of sensitivity and 92.71% of specificity. CONCLUSIONS: The obtained classification results are similar to (or even higher than) other studies that classify AD compared to CN individuals and comparable to those classified patients with MCI.