Nanostructured gadolinium (III) micelles: Synthesis, characterization, cytotoxic activities, and MRI applications in vivo.

Gadolinium-based contrast agents (GBCAs) are used in around 40 % of MRI procedures. Despite initial perceptions of minimal risk, their long-term use has emphasized the need to reduce toxicity and develop more efficient GBCAs with extended blood retention. Advancements in nanomaterials have led to improved GBCAs, enhancing MRI diagnostics. This study synthesizes and characterizes nanostructured gadolinium(III) micelles as superior MRI contrast agents. The complexes, [Gd(L)2], where L is a ligand of the N-alkyl-N-methylglucamine surfactant series (L8, L10 or L12, L10), form nanostructured micelles in aqueous solution. Gd(L8)2 and Gd(L10)2 relaxivities remained stable across concentrations. Compared to Gd-DTPA, Gd(III) micelles showed enhanced T1-weighted MRI contrast. Gd(L12)2 micelles exhibited cytotoxicity against B16F10 melanoma cells (IC50 42.5 ±â€¯2.2 µM) and L292L929 fibroblasts (IC50 52.0 ±â€¯2.5 µM), with a selectivity index of 1.2. In vivo application in mice brain T2-weighted images suggests nanostructured Gd(III) micelles are promising MRI contrast agents for targeting healthy organs or tumors.

Network-motif delay differential analysis of brain activity during seizures.

Delay Differential Analysis (DDA) is a nonlinear method for analyzing time series based on principles from nonlinear dynamical systems. DDA is extended here to incorporate network aspects to improve the dynamical characterization of complex systems. To demonstrate its effectiveness, DDA with network capabilities was first applied to the well-known Rössler system under different parameter regimes and noise conditions. Network-motif DDA, based on cortical regions, was then applied to invasive intracranial electroencephalographic data from drug-resistant epilepsy patients undergoing presurgical monitoring. The directional network motifs between brain areas that emerge from this analysis change dramatically before, during, and after seizures. Neural systems provide a rich source of complex data, arising from varying internal states generated by network interactions.

Lorenz-like systems and Lorenz-like attractors: Definition, examples, and equivalences.

Since the early 1970s, numerous systems exhibiting an algebraic structure resembling that of the 1963 Lorenz system have been proposed. These systems have occasionally yielded the same attractor as the Lorenz system, while in other cases, they have not. Conversely, some systems that are evidently distinct from the Lorenz system, particularly in terms of symmetry, have resulted in attractors that bear a resemblance to the Lorenz attractor. In this paper, we put forward a definition for Lorenz-like systems and Lorenz-like attractors. The former definition is based on the algebraic structure of the governing equations, while the latter relies on topological characterization. Our analysis encompasses over 20 explicitly examined chaotic systems.

Transformations that preserve the uniqueness of the differential form for Lorenz-like systems.

Differential equations serve as models for many physical systems. But, are these equations unique? We prove here that when a 3D system of ordinary differential equations for a dynamical system is transformed to the jerk or differential form, the jerk form is preserved in relation to a given variable and, therefore, the transformed system shares the time series of that given variable with the original untransformed system. Multiple algebraically different systems of ordinary differential equations can share the same jerk form. They may also share the same time series of the transformed variable depending on the parameters of the jerk form. Here, we studied 17 algebraically different Lorenz-like systems that share the same functional jerk form. There are groups of these systems that share the jerk parameters and, therefore, also have the same time series of the transformed variable.

A novel algorithm to assess the quality of 12-lead ECG recordings: validation in a real telecardiology application.

Objective. Automatic detection of Electrocardiograms (ECG) quality is fundamental to minimize costs and risks related to delayed diagnosis due to low ECG quality. Most algorithms to assess ECG quality include non-intuitive parameters. Also, they were developed using data non-representative of a real-world scenario, in terms of pathological ECGs and overrepresentation of low-quality ECG. Therefore, we introduce an algorithm to assess 12-lead ECG quality, Noise Automatic Classification Algorithm (NACA) developed in Telehealth Network of Minas Gerais (TNMG).Approach. NACA estimates a signal-to-noise ratio (SNR) for each ECG lead, where 'signal' is an estimated heartbeat template, and 'noise' is the discrepancy between the template and the ECG heartbeat. Then, clinically-inspired rules based on SNR are used to classify the ECG as acceptable or unacceptable. NACA was compared with Quality Measurement Algorithm (QMA), the winner of Computing in Cardiology Challenge 2011 (ChallengeCinC) by using five metrics: sensitivity (Se), specificity (Sp), positive predictive value (PPV),F2, and cost reduction resulting from adoption of the algorithm. Two datasets were used for validation: TestTNMG, consisting of 34 310 ECGs received by TNMG (1% unacceptable and 50% pathological); ChallengeCinC, consisting of 1000 ECGs (23% unacceptable, higher than real-world scenario).Main results. Both algorithms reached a similar performance on ChallengeCinC, although NACA performed considerably better than QMA in TestTNMG (Se = 0.89 versus 0.21; Sp = 0.99 versus 0.98; PPV = 0.59 versus 0.08;F2= 0.76 versus 0.16 and cost reduction 2.3 ± 1.8% versus 0.3 ± 0.3%, respectively).Significance. Implementing of NACA in a telecardiology service results in evident health and financial benefits for the patients and the healthcare system.

Diffeomorphical equivalence vs topological equivalence among Sprott systems.

In 1994, Sprott [Phys. Rev. E 50, 647-650 (1994)] proposed a set of 19 different simple dynamical systems producing chaotic attractors. Among them, 14 systems have a single nonlinear term. To the best of our knowledge, their diffeomorphical equivalence and the topological equivalence of their chaotic attractors were never systematically investigated. This is the aim of this paper. We here propose to check their diffeomorphical equivalence through the jerk functions, which are obtained when the system is rewritten in terms of one of the variables and its first two derivatives (two systems are thus diffeomorphically equivalent when they have exactly the same jerk function, that is, the same functional form and the same coefficients). The chaotic attractors produced by these systems-for parameter values close to the ones initially proposed by Sprott-are characterized by a branched manifold. Systems B and C produce chaotic attractors, which are observed in the Lorenz system and are also briefly discussed. Those systems are classified according to their diffeomorphical and topological equivalence.

Behavioral and EEGraphic Characterization of the Anticonvulsant Effects of the Predator Odor (TMT) in the Amygdala Rapid Kindling, a Model of Temporal Lobe Epilepsy.

Background: Clinical and experimental evidence indicates that olfactory stimulation modulates limbic seizures, either blocking or inducing ictal activity. Objective: We aim to evaluate the behavioral and electroencephalographic (EEGraphic) effects of dihydro-2,4,5-trimethylthiazoline (TMT) olfactory exposure on limbic seizures induced by amygdala rapid kindling (ARK). Materials and Methods: Wistar male rats (280-300 g) underwent stereotaxic surgery for electrode implantation in piriform cortex (PC), hippocampal formation (HIP), and amygdaloid complex (AMYG). Part of the animals was exposed to a saturated chamber with water or TMT, while others had ARK and olfactory exposure prior to the 21st stimulus. Behavioral responses were measured by traditional seizure severity scales (Racine and Pinel and Rovner) and/or by sequential analysis/neuroethology. The electrographic activity of epileptogenic limbic networks was quantified by the occurrence of the first and second EEG afterdischarges, comparing the 1st and 21st stimulus. The spectral analysis [Fast Fourier Transform (FFT)] of the first afterdischarge was performed at the 21st stimulus. Results: TMT olfactory exposure reduced the seizure severity in kindled rats, altering the displayed behavioral sequence. Moreover, TMT decreased the occurrence of first and second afterdischarges, at the 21st stimulus, and altered the spectral features. Conclusions: Both behavioral and EEGraphic evaluations indicated that TMT, a potent molecule with strong biological relevance, in fact, "predator odor," suppressed the epileptiform activity in limbic networks.

Pro-neurogenic effect of fluoxetine in the olfactory bulb is concomitant to improvements in social memory and depressive-like behavior of socially isolated mice.

Although loneliness is a human experience, it can be estimated in laboratory animals deprived from physical contact with conspecifics. Rodents under social isolation (SI) tend to develop emotional distress and cognitive impairment. However, it is still to be determined whether those conditions present a common neural mechanism. Here, we conducted a series of behavioral, morphological, and neurochemical analyses in adult mice that underwent to 1 week of SI. We observed that SI mice display a depressive-like state that can be prevented by enriched environment, and the antidepressants fluoxetine (FLX) and desipramine (DES). Interestingly, chronic administration of FLX, but not DES, was able to counteract the deleterious effect of SI on social memory. We also analyzed cell proliferation, neurogenesis, and astrogenesis after the treatment with antidepressants. Our results showed that the olfactory bulb (OB) was the neurogenic niche with the highest increase in neurogenesis after the treatment with FLX. Considering that after FLX treatment social memory was rescued and depressive-like behavior decreased, we propose neurogenesis in the OB as a possible mechanism to unify the FLX ability to counteract the deleterious effect of SI.

In-depth characterization of congenital Zika syndrome in immunocompetent mice: Antibody-dependent enhancement and an antiviral peptide therapy.

BACKGROUND: Zika virus (ZIKV) infection during pregnancy may cause major congenital defects, including microcephaly, ocular, articular and muscle abnormalities, which are collectively defined as Congenital Zika Syndrome. Here, we performed an in-depth characterization of the effects of congenital ZIKV infection (CZI) in immunocompetent mice. METHODS: Pregnant dams were inoculated with ZIKV on embryonic day 5.5 in the presence or absence of a sub-neutralizing dose of a pan-flavivirus monoclonal antibody (4G2) to evaluate the potential role of antibody-dependent enhancement phenomenon (ADE) during short and long outcomes of CZI. FINDINGS: ZIKV infection induced maternal immune activation (MIA), which was associated with occurrence of foetal abnormalities and death. Therapeutic administration of AH-D antiviral peptide during the early stages of pregnancy prevented ZIKV replication and death of offspring. In the post-natal period, CZI was associated with a decrease in whole brain volume, ophthalmologic abnormalities, changes in testicular morphology, and disruption in bone microarchitecture. Some alterations were enhanced in the presence of 4G2 antibody. INTERPRETATION: Our results reveal that early maternal ZIKV infection causes several birth defects in immunocompetent mice, which can be potentiated by ADE phenomenon and are associated with MIA. Additionally, antiviral treatment with AH-D peptide may be beneficial during early maternal ZIKV infection. FUND: This work was supported by the Brazilian National Science Council (CNPq, Brazil), Minas Gerais Foundation for Science (FAPEMIG), Funding Authority for Studies and Projects (FINEP), Coordination of Superior Level Staff Improvement (CAPES), National Research Foundation of Singapore and Centre for Precision Biology at Nanyang Technological University.

Classification of auditory selective attention using spatial coherence and modular attention index.

BACKGROUND AND OBJECTIVE: Brain-Computer Interfaces (BCIs) based on auditory selective attention have been receiving much attention because i) they are useful for completely paralyzed users since they do not require muscular effort or gaze and ii) focusing attention is a natural human ability. Several techniques - such as recently developed Spatial Coherence (SC) - have been proposed in order to optimize the BCI procedure. Thus, this work aims at investigating and comparing two strategies based on spatial coherence detection: contralateral and modular classifiers. The latter is a new method using modular attention index. The new classifier was developed to implement an auditory BCI where a volunteer makes binary choices using selective attention under the amplitude-modulated tones stimulation. METHODS: Contralateral and modular classifiers were applied to the electroencephalogram (EEG) recorded from 144 subjects under the BCI protocol. The best set of parameters (carriers of the stimulus, channels and trials of signal) for this BCI was investigated taking into consideration the hit rate and the information transfer rate. RESULTS: The best result obtained using the modular classifier was a hit rate of 91.67% and information transfer rate of 6.74 bits/min using 0.5 kHz/4.0 kHz as stimuli and three windows (5.10 sec of EEG signal). These results were obtained with five electrodes (C3, P3, F8, P4, O2) using exhaustive search to identify regions with greater coherence. CONCLUSION: The modular classifier - using electroencephalogram channels from the central, frontal, occipital and parietal areas - improves the performance of auditory BCIs based on selective attention.

Inhibiting constitutive neurogenesis compromises long-term social recognition memory.

Although the functional role for newborn neurons in neural circuits is still matter of investigation, there is no doubt that neurogenesis modulates learning and memory in rodents. In general, boosting neurogenesis before learning, using genetic-target tools or drugs, improves hippocampus-dependent memories. However, inhibiting neurogenesis may yield contradictory results depending on the type of memory evaluated. Here we tested the hypothesis that inhibiting constitutive neurogenesis would compromise social recognition memory (SRM). Male Swiss mice were submitted to three distinct procedures to inhibit neurogenesis: (1) intra-cerebral infusion of Cystosine-ß-D-Arabinofuranoside (AraC); (2) intra-peritoneal injection of temozolomide (TMZ) and (3) cranial gamma irradiation. All three methods decreased cell proliferation and neurogenesis in the dentate gyrus of the dorsal (dDG) and ventral hippocampus (vDG), and the olfactory bulb (OB). However, the percentage inhibition diverged between methods and brain regions. Ara-C, TMZ and gamma irradiation impaired SRM, though only gamma irradiation did not cause side effects on weight gain, locomotor activity and anxiety. Finally, we examined the contribution of cell proliferation in vDG, dDG and OB to SRM. The percent of inhibition in the dDG correlates with SRM, independently of the method utilized. This correlation was observed for granular cell layer of OB and vDG, only when the inhibition was induced by gamma irradiation. Animal's performance was restrained by the inhibition of dDG cell proliferation, suggesting that cell proliferation in the dDG has a greater contribution to SRM. Altogether, our results demonstrate that SRM, similarly to other hippocampus-dependent memories, has its formation impaired by reducing constitutive neurogenesis.

A novel approach for accelerating mouse abdominal MRI by combining respiratory gating and compressed sensing.

PURPOSE: To combine the technique of respiratory gating and compressed sensing (CS) with the objective of accelerating mouse abdominal magnetic resonance imaging (MRI). MATERIALS AND METHODS: To obtain the maximum acceleration, phase-encoding data from a phantom and mouse were obtained on a 4.7 Tesla scanner using the respiratory gating technique. The fully sampled data (FSD) were used to construct reference images and to provide samples to simulate retrospective undersampled data (UD) acquisition using respiratory gating. The UD and 95% of the UD on acceleration 2-5 rates were acquired and used for image reconstruction by CS. Quantitative assessment of reconstructed images was performed by structural similarity index (SSIM), peak signal-to-noise ratio (PSNR) and root mean square error (RMSE). RESULTS: The proposed method can accelerate phantom and mouse abdominal MRI acquisition between 2 and 4 rates by reducing the amount of FSD. For phantom UD acquisition, the mean time was reduced in 45.9% and for the acquisition of 95% of UD in 67.8%. For mouse abdominal image UD acquisition, the mean time was reduced in 44.6% and for the acquisition of 95% of UD in 62.5%. The metrics results show that the reconstructed image from UD and 95% of UD by using CS maintains an optimal agreement with their reference images (similarity above 0.88 for phantom and 0.93 for mouse). CONCLUSION: This study presents a novel approach to accelerate mouse abdominal MRI combining respiratory gating technique and CS without the use of expensive hardware and capable of achieving up to 4 acceleration rate without image degradation.

Multivariate evoked response detection based on the spectral F-test.

BACKGROUND: Objective response detection techniques, such as magnitude square coherence, component synchrony measure, and the spectral F-test, have been used to automate the detection of evoked responses. The performance of these detectors depends on both the signal-to-noise ratio (SNR) and the length of the electroencephalogram (EEG) signal. NEW METHOD: Recently, multivariate detectors were developed to increase the detection rate even in the case of a low signal-to-noise ratio or of short data records originated from EEG signals. In this context, an extension to the multivariate case of the spectral F-test detector is proposed. RESULTS: The performance of this technique is assessed using Monte Carlo. As an example, EEG data from 12 subjects during photic stimulation is used to demonstrate the usefulness of the proposed detector. COMPARISON WITH EXISTING METHOD(S): The multivariate method showed detection rates consistently higher than those ones when only one signal was used. CONCLUSIONS: It is shown that the response detection in EEG signals with the multivariate technique was statistically significant if two or more EEG derivations were used.

Non-parametric kernel density estimation for the prediction of neoadjuvant chemotherapy outcomes.

In this paper we propose an application of local statistical models to the problem of identifying patients with pathologic complete response (PCR) to neoadjuvant chemotherapy. The idea of using local models is to split the input space (with data from PCR and NoPCR patients) and build a model for each partition. After the construction of the models we used bayesian classifiers and logistic regression to classify patients in the two classes.

Testing for intracycle determinism in pseudoperiodic time series.

A determinism test is proposed based on the well-known method of the surrogate data. Assuming predictability to be a signature of determinism, the proposed method checks for intracycle (e.g., short-term) determinism in the pseudoperiodic time series for which standard methods of surrogate analysis do not apply. The approach presented is composed of two steps. First, the data are preprocessed to reduce the effects of seasonal and trend components. Second, standard tests of surrogate analysis can then be used. The determinism test is applied to simulated and experimental pseudoperiodic time series and the results show the applicability of the proposed test.

Robust discretizations versus increase of the time step for the Lorenz system.

When continuous systems are discretized, their solutions depend on the time step chosen a priori. Such solutions are not necessarily spurious in the sense that they can still correspond to a solution of the differential equations but with a displacement in the parameter space. Consequently, it is of great interest to obtain discrete equations which are robust even when the discretization time step is large. In this paper, different discretizations of the Lorenz system are discussed versus the values of the discretization time step. It is shown that the sets of difference equations proposed are more robust versus increases of the time step than conventional discretizations built with standard schemes such as the forward Euler, backward Euler, or centered finite difference schemes. The nonstandard schemes used here are Mickens' scheme and Monaco and Normand-Cyrot's scheme.

A note on discretization of nonlinear differential equations.

An important issue when integrating nonlinear differential equations on a digital computer is the choice of the time increment or step size. For example, it is known that if this quantity is not sufficiently short, spurious chaotic motions may be induced when integrating a system using several of the well-known methods available in the literature. In this paper, a new approach to discretize differential equations is analyzed in light of computational chaos. It will be shown that the fixed points of the continuous system are preserved under the new discretization approach and that the spurious fixed points generated by higher order approximations depend upon the increment parameter. (c) 2002 American Institute of Physics.