Month: November 2022

Alzheimer’s disease (AD), characterized by an accumulation of β-amyloid protein (Aβ) in brain tissue, is a leading cause of dementia. Researchers at Tokyo University of Science have previously reported on the oxytocin-induced reversal of impaired synaptic plasticity triggered by amyloid β peptide (25-35) (Aβ25-35). They now show that an oxytocin derivative with modifications to enhance brain perfusion can reverse Aβ25-35-induced cognitive impairment in mice.

The cognitive decline and memory loss observed in Alzheimer’s disease (AD) is attributed to the accumulation of β-amyloid protein (Aβ), which impairs neural function in the brain. Experimentation has shown that oxytocin, a peptide hormone primarily responsible for parturition, bonding, and lactation, also regulates cognitive behavior in the rodent central nervous system (CNS). This finding, along with the identification of oxytocin receptors in CNS neurons, has spurred interest in the potential role of oxytocin in reversing memory loss tied to cognitive disorders like AD.

However, peptides like oxytocin are characterized by weak blood-brain barrier permeability, and so can only by efficiently delivered to the brain via intracerebroventricular (ICV) administration. ICV, however, is an invasive technique which is impractical to implement clinically.

Delivering peptides to the CNS via intranasal (IN) administration is a viable clinical option. Prof. Chikamasa Yamashita at Tokyo University of Science recently patented a method to increase the efficiency of peptide delivery to the brain, by introducing cell-penetrating peptides (CPPs) and a penetration accelerating sequence (PAS) through structural modifications. Previous work had confirmed that both CPPs and the PAS benefit the nose-to-brain delivery pathway. Now, a group of researchers, led by Prof. Akiyoshi Saitoh and Prof. Jun-Ichiro Oka, leveraged this approach to prepare an oxytocin derivative: PAS-CPPs-oxytocin. Their findings were published online in Neuropsychopharmacology Reports on 19 September 2022.

“We have previously shown that oxytocin reverses amyloid β peptide (25-35) (Aβ25-35)-induced impairment of synaptic plasticity in rodents. We wanted to see if PAS-CPPs-oxytocin could be delivered more efficiently to the mouse brain for clinical application, and if it improved cognitive functional behavior in mice,” states Prof. Oka.

The group first developed an Aβ25-35 peptide-induced amnesia model by supplying Aβ25-35 to the mouse brain using ICV delivery. During the course of the study, the spatial working and spatial reference memories of these mice were evaluated using the Y-maze and Morris water maze (MWM) tests. After confirming that memory was affected in Aβ25-35-impaired mice, PAS-CPPs-oxytocin and native oxytocin were administered using the IN and ICV routes respectively, to see if learning and memory improved in the treated mice. Finally, the distribution of the IN-administered oxytocin derivative in brain tissue was profiled by imaging of a fluorescent-tagged oxytocin derivative.

The results of this study were quite promising! The tagged PAS-CPPs-oxytocin showed distribution throughout the mouse brain following its IN administration. While the ICV administration of native oxytocin improved test outcomes in both the Y-maze and MWM tests, the IN administered PAS-CPPs-oxytocin yielded memory improving effects in the Y-maze test. Hailing the team’s discovery, Prof. Oka says, “My team is the first to show that the oxytocin derivative can improve the Aβ25-35-induced memory impairment in mice. This suggests that oxytocin may help reduce the cognitive decline we see in Alzheimer’s disease.”

Why are these findings clinically useful? Prof. Oka explains the broader implications of their work, “The oxytocin derivative enters the brain more efficiently. Furthermore, since IN delivery is a non-invasive procedure, this modified version of the hormone could potentially be a clinically viable treatment for Alzheimer’s disease.”

Researchers effectively tune the parameters of a perturbation method to preserve chaos in the Bernoulli shift map output

The Bernoulli shift map is a well-known chaotic map in chaos theory. For a binary system, however, the output is not chaotic and converges to zero instead. One way to prevent this is by perturbing the state space of the map. In a new study, researchers explore one such perturbation method to obtain non-converging outputs with long periods and analyze these periods using modular arithmetic, obtaining a complete list of parameter values for optimal perturbations.

Is it possible for a deterministic system to be unpredictable? Although counter-intuitive, the answer is yes. Such systems are called “chaotic systems,” which are characterized by sensitive dependence on initial conditions and long-term unpredictability. The behavior of such systems is often described using what is known as a “chaotic map.” Chaotic maps finds applications in areas such as algorithm design, data analysis, and numerical simulations.

One well-known example of a chaotic map is the Bernoulli shift map. In practical applications of the Bernoulli shift map, the outputs are often required to have long periods. Strangely enough, however, when the Bernoulli shift map is implemented in a binary system, such as a digital computer, the output sequence is no longer chaotic and instead converges to zero!

To this end, perturbation methods are an effective strategy where a disturbance is applied to the state of the Bernoulli shift map to prevent its output from converging. However, the choice of parameters for obtaining suitable perturbations lacks a theoretical underpinning.

In a recent study made available online on October 21, 2022 and published in Volume 165, Part 1 of the journal Chaos, Solitons & Fractals on December 2022, Professor Tohru Ikeguchi from the Tokyo University of Science in association with Dr. Noriyoshi Sukegawa from University of Tsukuba, both in Japan, have now addressed this issue, laying the theoretical foundations for effective parameter tuning. “While numerical simulations can tell us which values of the parameters can prevent convergence, there is no theoretical background for choosing these values. In this paper, we aimed to investigate the theoretical support behind this choice,” explains Prof. Ikeguchi.

Accordingly, the researchers made use of modular arithmetic to tune a dominant parameter in the perturbation method. In particular, they defined the best value for the parameter, which depended on the bit length specified in implementations. The team further analyzed the output period for which the parameter had the best value. Their findings showed that the resulting periods came close to the trivial theoretical upper bounds. Based on this, the researchers obtained a complete list of the best parameter values for a successful implementation of the Bernoulli shift map.

Additionally, an interesting consequence of their investigation was its relation to Artin’s conjecture on primitive roots, an open question in number theory. The researchers suggested that, provided Artin’s conjecture were true, their approach would be theoretically guaranteed to be effective for any bit length.

Overall, the theoretical foundations put forth in this research are of paramount importance in the practical applications of chaotic maps in general. “A notable advantage of our approach is that it provides a theoretical support to the choice of best parameters. In addition, our analysis can also be partially applied to other chaotic maps, such as the tent map and the logistic map,” highlights Dr. Sukegawa.

With distinct advantages, such as simplicity and ease of implementation, the Bernoulli shift maps is highly desirable in several practical applications. And, as this study shows, sometimes chaos is preferable to order!