Neural Membrane Research Articles

Hybrid stem cell-derived bioresponsive vesicles for effective inflamed blood-brain barrier targeting delivery

Blood-brain barrier (BBB) dis-integrity, a characteristic of extensive inflammatory encephalopathy, provides the access for brain-targeted drug delivery. Inspired from the bioresponsiveness of stem cell, we conceived of new nano-scale delivery strategy via neural stem cell membrane-derived bioresponsive vesicles (NSC-Lipo) for inflamed BBB target delivery. After recombination of neural stem cell membranes with simple liposomes, the functional ligands, especially very late antigen-4 (VLA-4), were entirely engrafted into NSC-Lipo and equipped the NSC-Lipo with “pass order” to the “selective gate”. It bestowed the bioresponsive vesicles with selective target the injured brain microvessel endothelial cells (BMECs) and penetrate into the lesion through the vascular cell adhesion molecule-1 (VCAM-1)/VLA-4 interaction in the post-ischemic mice model. The released anti-inflammatory agent, metformin, could reverse the inflammatory response of BMECs and rapidly recovers BBB’s integrity. With the repair of BBB’s integrity and down regulation of VCAM-1 expression, the targeting ability of bioresponsive vesicles cease to be in force as well. The bioresponsive vesicles led to enhanced survival rate of ischemic stroke mice (from 30 % to 90 %) after just a single injection compared to metformin loaded bare liposomes.

Dendritic plateau potentials can process spike sequences across multiple time-scales

The brain constantly processes information encoded in temporal sequences of spiking activity. This sequential activity emerges from sensory inputs as well as from the brain's own recurrent connectivity and spans multiple dynamically changing timescales. Decoding the temporal order of spiking activity across these varying timescales is a critical function of the brain, but we do not yet understand its neural implementation. The problem is, that the passive dynamics of neural membrane potentials occur on a short millisecond timescale, whereas many cognitive tasks require the integration of information across much slower behavioral timescales. However, actively generated dendritic plateau potentials do occur on such longer timescales, and their essential role for many aspects of cognition has been firmly established by recent experiments. Here, we build on these discoveries and propose a new model of neural computation that emerges from the interaction of localized plateau potentials across a functionally compartmentalized dendritic tree. We show how this interaction offers a robust solution to the timing invariant detection and processing of sequential spike patterns in single neurons. Stochastic synaptic transmission complements the deterministic all-or-none plateau process and improves information transmission by allowing ensembles of neurons to produce graded responses to continuous combinations of features. We found that networks of such neurons can solve highly complex sequence detection tasks by breaking down long inputs into sequences of shorter, random features that can be classified reliably. These results suggest that active dendritic processes are fundamental to neural computation.

Plasma brain derived neurotrophic factor level as a modifying factor for trans fat intake and hypertension

Long-term consumption of trans-fat has been linked with its incorporation in brain neural membrane that could lead into alteration of signalling pathways, including Brain Derived Neurotrophic Factor (BDNF). As an ubiquitous neurotrophin, BDNF is believed to play a role in the regulation of blood pressure yet prior studies shown conflicting results to its effect. Moreover, direct effect of trans fat intake to hypertension has not yet been elucidated. This study aimed to investigate the role of BDNF and its association between trans-fat intake and hypertension. We conducted a population study in Natuna Regency which once reportedly has the highest prevalence of hypertension from Indonesian National Health Survey. Subjects with hypertension and those without hypertension were recruited for the study. Demographic data, physical examination, and food recall were collected. The level of BDNF from all subjects were obtained through analysis of blood samples. A total of 181 participants were included in this study, comprising 134 (74%) hypertensive subjects and 47 (26%) normotensive subjects. Median of daily trans-fat intake of hypertensive subjects was higher compared to normotensive subjects (0,013 [0,0003-0,07] vs 0,010 [0,0006-0,06] % of total energy/day, p=0,021). Interaction analysis showed significant results for plasma BDNF level in relationship of trans-fat intake and hypertension (p=0,011). Trans-fat intake association to hypertension in overall subjects showed odds ratio (OR) of 1,85 95%CI 1,05-3,26 (p=0,034), while in those with low-middle tercile BDNF level the OR was 3,35 95%CI 1,46-7,68 (p=0,004). Plasma BDNF level has a modifying effect in the association between trans-fat intake and hypertension. Subjects with high trans-fat intake, while having low BDNF level, have the highest probability for hypertension.

Structural basis of botulinum neurotoxin serotype A1 binding to human SV2A or SV2C receptors

Botulinum neurotoxin A1 (BoNT/A1) is the most potent natural poison in human. BoNT/A1 recognize the luminal domain of SV2A (LD-SV2A) and its glycosylation at position N573 (N573g) or the luminal domain of SV2C (LD-SV2C) and its glycosylation at position N559 (N559g) to bind neural membrane. Our computational data suggest that the N-glycan at position 480 (N480g) in the luminal domain of SV2C (LD-SV2C) indirectly enhanced the contacts of the neurotoxin surface with the second N-glycan at position 559 (N559g) by acting as a shield to prevent N559g to interact with residues of LD-SV2C. The absence of an N-glycan homologous to N480g in LD-SV2A leads to a decrease of the binding of N573g to the surface of BoNT/A1. Concerning the intermolecular interactions between BoNT/A and the protein part of LD-SV2A or LD-SV2C, we showed that the high affinity of the neurotoxin for binding LD-SV2C are mediated by a better compaction of its F557–F562 part provided by a π-π network mediated by residues F547, F552, F557 and F562 coupled with the presence of two aromatic residues at position 563 and 564 that optimize the binding of BoNT/A1 via cation-pi and CH-pi interaction. Finally, in addition to the well-known ganglioside binding site which accommodates a ganglioside on the surface of BoNT/A1, we identified a structure we coined the ganglioside binding loop defined by the sequence 1253-HQFNNIAK-1260 that is conserved across all subtypes of BoNT/A and is predicted to has a high affinity to interact with gangliosides. These data solved the puzzle generated by mutational studies that could be only partially understood with crystallographic data that lack both a biologically relevant membrane environment and a full glycosylation of SV2.

Ether Lipid-Mediated Antioxidant Defense in Alzheimer's Disease.

One of the richest tissues in lipid content and diversity of the human body is the brain. The human brain is constitutively highly vulnerable to oxidative stress. This oxidative stress is a determinant in brain aging, as well as in the onset and progression of sporadic (late-onset) Alzheimer's disease (sAD). Glycerophospholipids are the main lipid category widely distributed in neural cell membranes, with a very significant presence for the ether lipid subclass. Ether lipids have played a key role in the evolution of the human brain compositional specificity and functionality. Ether lipids determine the neural membrane structural and functional properties, membrane trafficking, cell signaling and antioxidant defense mechanisms. Here, we explore the idea that ether lipids actively participate in the pathogenesis of sAD. Firstly, we evaluate the quantitative relevance of ether lipids in the human brain composition, as well as their role in the human brain evolution. Then, we analyze the implications of ether lipids in neural cell physiology, highlighting their inherent antioxidant properties. Finally, we discuss changes in ether lipid content associated with sAD and their physiopathological implications, and propose a mechanism that, as a vicious cycle, explains the potential significance of ether lipids in sAD.

An Antisense Oligonucleotide-Loaded Blood-Brain Barrier Penetrable Nanoparticle Mediating Recruitment of Endogenous Neural Stem Cells for the Treatment of Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disease characterized by the death of dopaminergic (DA) neurons and currently cannot be cured. One selected antisense oligonucleotide (ASO) is reported to be effective for the treatment of PD. However, ASO is usually intrathecally administered by lumbar puncture into the cerebral spinal fluid, through which the risks of highly invasive neurosurgery are the major concerns. In this study, ZAAM, an ASO-loaded, aptamer Apt 19S-conjugated, neural stem cell membrane (NSCM)-coated nanoparticle (NP), was developed for the targeted treatment of PD. NSCM facilitated the blood-brain barrier (BBB) penetration of NPs, and both NSCM and Apt 19S promoted the recruitment of the neural stem cells (NSCs) toward the PD site for DA neuron regeneration. The behavioral tests demonstrated that ZAAM highly improved the efficacy of ASO on PD by the targeted delivery of ASO and the recruitment of NSCs. This work is a heuristic report of (1) nonchemoattractant induced endogenous NSC recruitment, (2) NSCM-coated nanoparticles for the treatment of neurodegenerative diseases, and (3) systemic delivery of ASO for the treatment of PD. These findings provide insights into the development of biomimetic BBB penetrable drug carriers for precise diagnosis and therapy of central nervous system diseases.

Vertebral artery is an anatomical landmark in the posterior unilateral resection of cervical benign nerve sheath tumors with dumbbell extension of Eden type 2 or 3.

In the cervical nerve sheath tumor (NST) surgery with dumbbell extension of Eden type 2 or 3, selection of anterior, posterior, or combined approach remains controversial. This technical note aimed to propose possible advantages of the posterior unilateral approach (PUA). Methods: Six patients who underwent the surgical treatment of cervical NSTs with dumbbell extension of Eden type 2 or 3 were included. The critical surgical steps included (1) complete separation of extradural and intradural procedures, (2) careful peeling of the neural membranes (epineurium and perineurium) from the tumor surface in the extradural procedure, (3) complete removal of the extradural tumor within the neural membranes, (4) intradural disconnection of tumor origin, and (5) intentional tumor removal up to the vertebral artery (VA), i.e., the VA line. The tumor location of dumbbell extension was Eden types 2 and 3 in two and four patients. Gross total resection was achieved in two patients and intentional posterior removal of the tumor to the VA line was achieved in the remaining four patients. No vascular or neural injuries associated with surgical procedures occurred. Postoperative neurological assessment revealed no symptomatic aggravation in all patients. No secondary surgery was performed during the study period. PUA was safe and less invasive for functional recovery and tumor resection, if the anatomical relationship between the tumor and VA is clearly understood. The VA line is an important anatomical landmark to limit the extent of tumor resection.

Annexin A3 levels in patients with schizophrenia and bipolar disorder

Schizophrenia and bipolar disorder are disorders characterized by alterations in cellular and molecular mechanisms. Annexin A3 (ANXA3) has various effects on neural mechanisms and membrane phospholipid function and both mechanisms are thought to be associated with psychotic disorders. Our study consisted of 93 schizophrenia and bipolar disorder and 52 healthy controls. ANXA3 was analyzed by enzyme-linked immunosorbent assay (ELISA). ANXA3 levels were significantly different between the groups (p<0.001). ANXA3 levels of the control group were higher than ANXA3 levels of schizophrenia and bipolar disorder groups (p<0.001, p<0.001). The ANXA3 levels of the bipolar group were higher than the ANXA3 levels of the schizophrenia group (p<0.001). Laboratory levels of B12, folate, vitamin D, glucose, urea, creatinine, prothrombin time (PT), gamma-glutamyl transferase and lactate dehydrogenase were compared between the groups. B12 levels of the schizophrenia group were lower than B12 levels of bipolar and control groups (p=0.05, p<0.001). Creatinine levels of the schizophrenia group were higher than the creatinine levels of the healthy group (p<0.05). According to posthoc test results, PT levels of the schizophrenia group were higher than PT levels of the healthy group (p<0.05). In line with these findings, we suggest that ANXA3 protein deficiency may have an important role in the physiopathology of schizophrenia and bipolar disorder and may be used as a biomarker in the diagnosis of some psychotic disorders.

Iron level changes in the brain with neurodegenerative disease

Nanosized magnetite inside ferritin may control the progression of neurodegenerative disease (ND) by creating an electronic noise in the neural cells. We discovered that brains with ND have a unique electron paramagnetic resonance (EPR) spectrum. Our measurements showed that the collapse of the broad ferritin maximum contained in the EPR spectra possibly relates to the onset and progression of the ND. Ferritin malfunction triggers the perturbation of iron concentration that either increases or decreases over the normal levels in brain without ND. This supports a conjecture that accumulated iron results in an increased volume of magnetite crystals, whose fluctuated magnetic moments may interfere with the normal function of neural synapses and contribute to the neurodegenerative disease. The mechanism of the iron mobility relates to iron canals in the neural cell's membrane by which the iron enters and leaves the neural cells. This gate keeper malfunction may relate to a speculation that this is due to the appearance of 2Fe-2S in EPR spectra of brains with ND. Statement of significanceIn this manuscript we describe feedback between electronic structure of atoms in the brain, easiness of becoming magnetized in a magnetic field and the ability of the brain to hold the magnetic field on its own in cases of neurodegenerative-diseased and healthy brain. This contribution is novel and significant for a number of reasons, as follows: We revealed that diseased brains have a distinct electronic structure from healthy brains. We identified the easiness of brain samples to become magnetized in a magnetic field and the brains’ ability to hold the magnetic field on its own in cases of neurodegenerative-diseased and healthy brains. This paper addresses a new hypothesis, and we consider that it will generate broad that may be of broad interdisciplinary interest and generate further debate.

Effect of high-frequency membrane potential alternation between depolarization and hyperpolarization on dorsal root ganglion neurons of rats.

The purpose of this study was to determine how sensory neurons respond to high-frequency membrane potential alternation between depolarization and hyperpolarization. Membrane currents were recorded from dissociated dorsal root ganglion (DRG) neurons of adult rats using the whole cell patch clamp technique in voltage clamp mode. Stepwise depolarization of the membrane was applied first to determine the threshold membrane potential for inducing an action potential (AP) current. Then, membrane potential alternation between depolarization (to +20 mV) and hyperpolarization (to -110 mV) was applied to the neuron for 10s at different frequencies (10 Hz to 1 kHz). The tested DRG neurons had APs of either a long duration (>10ms) or a short duration (<10ms). Membrane potential alternation at ≥500 Hz completely disrupted the AP generation, disabled the ion channel gating function, and produced membrane current alternating symmetrically across zero. Replacing extracellular sodium with potassium increased the amplitude of the membrane current response and caused the membrane current to be larger during hyperpolarization than during depolarization. These results support the hypothesis that high-frequency biphasic stimulation blocks axonal conduction by driving the potassium channel open constantly. Understanding neural membrane response to high-frequency membrane potential alternation is important to reveal the possible mechanisms underlying axonal conduction block induced by high-frequency biphasic stimulation.

Closed-loop optimal and automatic tuning of pulse amplitude and width in EMG-guided controllable transcranial magnetic stimulation.

This paper proposes an efficient algorithm for automatic and optimal tuning of pulse amplitude and width for sequential parameter estimation (SPE) of the neural membrane time constant and input-output (IO) curve parameters in closed-loop electromyography-guided (EMG-guided) controllable transcranial magnetic stimulation (cTMS). The proposed SPE is performed by administering a train of optimally tuned TMS pulses and updating the estimations until a stopping rule is satisfied or the maximum number of pulses is reached. The pulse amplitude is computed by the Fisher information maximization. The pulse width is chosen by maximizing a normalized depolarization factor, which is defined to separate the optimization and tuning of the pulse amplitude and width. The normalized depolarization factor maximization identifies the critical pulse width, which is an important parameter in the identifiability analysis, without any prior neurophysiological or anatomical knowledge of the neural membrane. The effectiveness of the proposed algorithm is evaluated through simulation. The results confirm satisfactory estimation of the membrane time constant and IO curve parameters for the simulation case. By defining the stopping rule based on the satisfaction of the convergence criterion with tolerance of 0.01 for 5 consecutive times for all parameters, the IO curve parameters are estimated with 52 TMS pulses, with absolute relative estimation errors (AREs) of less than 7%. The membrane time constant is estimated with 0.67% ARE, and the pulse width value tends to the critical pulse width with 0.16% ARE with 52 TMS pulses. The results confirm that the pulse width and amplitude can be tuned optimally and automatically to estimate the membrane time constant and IO curve parameters in real-time with closed-loop EMG-guided cTMS.

What Is the Evidence for Dietary-Induced DHA Deficiency in Human Brains?

Docosahexaenoic acid (DHA) is a major constituent of neural and visual membranes and is required for optimal neural and visual function. DHA is derived from food or by endogenous synthesis from α-linolenic acid (ALA), an essential fatty acid. Low blood levels of DHA in some westernised populations have led to speculations that child development disorders and various neurological conditions are associated with sub-optimal neural DHA levels, a proposition which has been supported by the supplement industry. This review searched for evidence of deficiency of DHA in human populations, based on elevated levels of the biochemical marker of n-3 deficiency, docosapentaenoic acid (22:5n-6). Three scenarios/situations were identified for the insufficient supply of DHA, namely in the brain of new-born infants fed with high-linoleic acid (LA), low-ALA formulas, in cord blood of women at birth who were vegetarians and in the milk of women from North Sudan. Twenty post-mortem brain studies from the developed world from adults with various neurological disorders revealed no evidence of raised levels of 22:5n-6, even in the samples with reduced DHA levels compared with control subjects. Human populations most likely at risk of n-3 deficiency are new-born and weanling infants, children and adolescents in areas of dryland agriculture, in famines, or are refugees, however, these populations have rarely been studied. This is an important topic for future research.

Formalizing the Use of the Activation Function in Neural Inference

We investigate how the activation function can be used to describe neural firing in an abstract way, and in turn, why it works well in artificial neural networks. We discuss how a spike in a biological neuron belongs to a particular universality class of phase transitions in statistical physics. We then show that the artificial neuron is, mathematically, a mean-field model of biological neural membrane dynamics, which arises from modeling spiking as a phase transition. This allows us to treat selective neural firing in an abstract way and formalize the role of the activation function in perceptron learning. The resultant statistical physical model allows us to recover the expressions for some known activation functions as various special cases. Along with deriving this model and specifying the analogous neural case, we analyze the phase transition to understand the physics of neural network learning. Together, it is shown that there is not only a biological meaning but a physical justification for the emergence and performance of typical activation functions; implications for neural learning and inference are also discussed.

Complement inhibition prevents glial nodal membrane injury in a GM1 antibody-mediated mouse model.

The involvement of the complement pathway in Guillain-Barré syndrome pathogenesis has been demonstrated in both patient biosamples and animal models. One proposed mechanism is that anti-ganglioside antibodies mediate neural membrane injury through the activation of complement and the formation of membrane attack complex pores, thereby allowing the uncontrolled influx of ions, including calcium, intracellularly. Calcium influx activates the calcium-dependent protease calpain, leading to the cleavage of neural cytoskeletal and transmembrane proteins and contributing to subsequent functional failure. Complement inhibition has been demonstrated to provide effective protection from injury in anti-ganglioside antibody-mediated mouse models of axonal variants of Guillain-Barré syndrome; however, the role of complement in the pathogenesis of demyelinating variants has yet to be established. Thus, it is currently unknown whether complement inhibition would be an effective therapeutic for Guillain-Barré syndrome patients with injuries to the Schwann cell membrane. To address this, we recently developed a mouse model whereby the Schwann cell membrane was selectively targeted with an anti-GM1 antibody resulting in significant disruption to the axo-glial junction and cytoplasmic paranodal loops, presenting as conduction block. Herein, we utilize this Schwann cell nodal membrane injury model to determine the relevance of inhibiting complement activation. We addressed the early complement component C2 as the therapeutic target within the complement cascade by using the anti-C2 humanized monoclonal antibody, ARGX-117. This anti-C2 antibody blocks the formation of C3 convertase, specifically inhibiting the classical and lectin complement pathways and preventing the production of downstream harmful anaphylatoxins (C3a and C5a) and membrane attack complexes. Here, we demonstrate that C2 inhibition significantly attenuates injury to paranodal proteins at the node of Ranvier and improves respiratory function in ex vivo and in vivo Schwann cell nodal membrane injury models. In parallel studies, C2 inhibition also protects axonal integrity in our well-established model of acute motor axonal neuropathy mediated by both mouse and human anti-GM1 antibodies. These data demonstrate that complement inhibition prevents injury in a Schwann cell nodal membrane injury model, which is representative of neuropathies associated with anti-GM1 antibodies, including Guillain-Barré syndrome and multifocal motor neuropathy. This outcome suggests that both the motor axonal and demyelinating variants of Guillain-Barré syndrome should be included in future complement inhibition clinical trials.

Enzymatic Numerical Spiking Neural Membrane Systems and their Application in Designing Membrane Controllers.

Spiking neural P systems (SN P systems), inspired by biological neurons, are introduced as symbolical neural-like computing models that encode information with multisets of symbolized spikes in neurons and process information by using spike-based rewriting rules. Inspired by neuronal activities affected by enzymes, a numerical variant of SN P systems called enzymatic numerical spiking neural P systems (ENSNP systems) is proposed wherein each neuron has a set of variables with real values and a set of enzymatic activation-production spiking rules, and each synapse has an assigned weight. By using spiking rules, ENSNP systems can directly implement mathematical methods based on real numbers and continuous functions. Furthermore, ENSNP systems are used to model ENSNP membrane controllers (ENSNP-MCs) for robots implementing wall following. The trajectories, distances from the wall, and wheel speeds of robots with ENSNP-MCs for wall following are compared with those of a robot with a membrane controller for wall following. The average error values of the designed ENSNP-MCs are compared with three recently fuzzy logical controllers with optimization algorithms for wall following. The experimental results showed that the designed ENSNP-MCs can be candidates as efficient controllers to control robots implementing the task of wall following.

A formalism for sequential estimation of neural membrane time constant and input–output curve towards selective and closed-loop transcranial magnetic stimulation * * Matlab Code is available at https://github.com/smmalavi/TMS-tau-IOC-estim-fixed-tp.

Objective. To obtain a formalism for real-time concurrent sequential estimation of neural membrane time constant and input–output (IO) curve with transcranial magnetic stimulation (TMS). Approach. First, the neural membrane response and depolarization factor, which leads to motor evoked potentials with TMS are analytically computed and discussed. Then, an integrated model is developed which combines the neural membrane time constant and IO curve. Identifiability of the proposed integrated model is discussed. A condition is derived, which assures estimation of the proposed integrated model. Finally, sequential parameter estimation (SPE) of the neural membrane time constant and IO curve is described through closed-loop optimal sampling and open-loop uniform sampling TMS. Without loss of generality, this paper focuses on a specific case of commercialized TMS pulse shapes. The proposed formalism and SPE method are directly applicable to other pulse shapes. Main results. The results confirm satisfactory estimation of the membrane time constant and IO curve parameters. By defining a stopping rule based on five times consecutive convergence of the estimation parameters with a tolerances of 0.01, the membrane time constant and IO curve parameters are estimated with 82 TMS pulses with absolute relative estimation errors (AREs) of less than 4% with the optimal sampling SPE method. At this point, the uniform sampling SPE method leads to AREs up to 16%. The uniform sampling method does not satisfy the stopping rule due to the large estimation variations. Significance. This paper provides a tool for real-time closed-loop SPE of the neural time constant and IO curve, which can contribute novel insights in TMS studies. SPE of the membrane time constant enables selective stimulation, which can be used for advanced brain research, precision medicine and personalized medicine.

Guanosine modulates K+ membrane currents in SH-SY5Y cells: involvement of adenosine receptors

Guanosine (GUO), widely considered a key signaling mediator, is implicated in the regulation of several cellular processes. While its interaction with neural membranes has been described, GUO still is an orphan neuromodulator. It has been postulated that GUO may eventually interact with potassium channels and adenosine (ADO) receptors (ARs), both particularly important for the control of cellular excitability. Accordingly, here, we investigated the effects of GUO on the bioelectric activity of human neuroblastoma SH-SY5Y cells by whole-cell patch-clamp recordings. We first explored the contribution of voltage-dependent K+ channels and, besides this, the role of ARs in the regulation of GUO-dependent cellular electrophysiology. Our data support that GUO is able to specifically modulate K+-dependent outward currents over cell membranes. Importantly, administering ADO along with GUO potentiates its effects. Overall, these results suggested that K+ outward membrane channels may be targeted by GUO with an implication of ADO receptors in SH-SY5Y cells, but also support the hypothesis of a functional interaction of the two ligands. The present research runs through the leitmotif of the deorphanization of GUO, adding insight on the interplay with adenosinergic signaling and suggesting GUO as a powerful modulator of SH-SY5Y excitability.

On the Tuning of the Computation Capability of Spiking Neural Membrane Systems with Communication on Request.

Spiking neural P systems (abbreviated as SNP systems) are models of computation that mimic the behavior of biological neurons. The spiking neural P systems with communication on request (abbreviated as SNQP systems) are a recently developed class of SNP system, where a neuron actively requests spikes from the neighboring neurons instead of passively receiving spikes. It is already known that small SNQP systems, with four unbounded neurons, can achieve Turing universality. In this context, 'unbounded' means that the number of spikes in a neuron is not capped. This work investigates the dependency of the number of unbounded neurons on the computation capability of SNQP systems. Specifically, we prove that (1) SNQP systems composed entirely of bounded neurons can characterize the family of finite sets of numbers; (2) SNQP systems containing two unbounded neurons are capable of generating the family of semilinear sets of numbers; (3) SNQP systems containing three unbounded neurons are capable of generating nonsemilinear sets of numbers. Moreover, it is obtained in a constructive way that SNQP systems with two unbounded neurons compute the operations of Boolean logic gates, i.e., OR, AND, NOT, and XOR gates. These theoretical findings demonstrate that the number of unbounded neurons is a key parameter that influences the computation capability of SNQP systems.

On Spiking Neural Membrane Systems with Neuron and Synapse Creation.

Spiking neural membrane systems are models of computation inspired by the natural functioning of the brain using the concepts of neurons and synapses, and represent a way of building computational systems of a biological inspiration. A variant of such a model, allowing to create new neurons and synapses during the computation, has been considered in the literature to attack computationally hard problems, like problems in the class NP. In this work, we investigate the computational properties of this variant, by proposing three solutions to computationally hard problems, by models with different features, and comparing them with those present in the literature. In particular, we first propose a nondeterministic solution for the NP-complete problem 3-SAT, by a model using dynamic organization of synapses. Then, we propose a deterministic solution for the same problem, by a model using neuron division and dissolution rules. Finally, we show that dissolution rules are not strictly necessary (by accepting a certain amount of slowdown in computing time), and that also problems beyond the class NP can be solved by systems with neuron division alone.

Interaction of Arginine-Rich Cell-Penetrating Peptides with an Artificial Neuronal Membrane.

Arginine-rich cell-penetrating peptides (RRCPPs) exhibit intrinsic neuroprotective effects on neurons injured by acute ischemic stroke. Conformational properties, interaction, and the ability to penetrate the neural membrane are critical for the neuroprotective effects of RRCCPs. In this study, we applied circular dichroism (CD) spectroscopy and coarse-grained molecular dynamics (CG MD) simulations to investigate the interactions of two RRCPPs, Tat(49–57)-NH2 (arginine-rich motif of Tat HIV-1 protein) and PTD4 (a less basic Ala-scan analog of the Tat peptide), with an artificial neuronal membrane (ANM). CD spectra showed that in an aqueous environment, such as phosphate-buffered saline, the peptides mostly adopted a random coil (PTD4) or a polyproline type II helical (Tat(49–57)-NH2) conformation. On the other hand, in the hydrophobic environment of the ANM liposomes, the peptides showed moderate conformational changes, especially around 200 nm, as indicated by CD curves. The changes induced by the liposomes were slightly more significant in the PTD4 peptide. However, the nature of the conformational changes could not be clearly defined. CG MD simulations showed that the peptides are quickly attracted to the neuronal lipid bilayer and bind preferentially to monosialotetrahexosylganglioside (DPG1) molecules. However, the peptides did not penetrate the membrane even at increasing concentrations. This suggests that the energy barrier required to break the strong peptide–lipid electrostatic interactions was not exceeded in the simulated models. The obtained results show a correlation between the potential of mean force parameter and a peptide’s cell membrane-penetrating ability and neuroprotective properties.