Targeting presynaptic H3 heteroreceptor in nucleus accumbens to improve anxiety and obsessive-compulsive-like behaviors.

Anxiety commonly co-occurs with obsessive-compulsive disorder (OCD). Both of them are closely related to stress. However, the shared neurobiological substrates and therapeutic targets remain unclear. Here we report an amelioration of both anxiety and OCD via the histamine presynaptic H3 heteroreceptor on glutamatergic afferent terminals from the prelimbic prefrontal cortex (PrL) to the nucleus accumbens (NAc) core, a vital node in the limbic loop. The NAc core receives direct hypothalamic histaminergic projections, and optogenetic activation of hypothalamic NAc core histaminergic afferents selectively suppresses glutamatergic rather than GABAergic synaptic transmission in the NAc core via the H3 receptor and thus produces an anxiolytic effect and improves anxiety- and obsessive-compulsive-like behaviors induced by restraint stress. Although the H3 receptor is expressed in glutamatergic afferent terminals from the PrL, basolateral amygdala (BLA), and ventral hippocampus (vHipp), rather than the thalamus, only the PrL- and not BLA- and vHipp-NAc core glutamatergic pathways among the glutamatergic afferent inputs to the NAc core is responsible for co-occurrence of anxiety- and obsessive-compulsive-like behaviors. Furthermore, activation of the H3 receptor ameliorates anxiety and obsessive-compulsive-like behaviors induced by optogenetic excitation of the PrL-NAc glutamatergic afferents. These results demonstrate a common mechanism regulating anxiety- and obsessive-compulsive-like behaviors and provide insight into the clinical treatment strategy for OCD with comorbid anxiety by targeting the histamine H3 receptor in the NAc core.

[Changes in sensitivity of bilateral medial vestibular nuclear neurons responding to input stimuli during vestibular compensation and the underlying ionic mechanism].

Vestibular compensation is an important model for developing the prevention and intervention strategies of vestibular disorders, and investigating the plasticity of the adult central nervous system induced by peripheral injury. Medial vestibular nucleus (MVN) in brainstem is critical center for vestibular compensation. Its neuronal excitability and sensitivity have been implicated in normal function of vestibular system. Previous studies mainly focused on the changes in neuronal excitability of the MVN in lesional side of the rat model of vestibular compensation following the unilateral labyrinthectomy (UL). However, the plasticity of sensitivity of bilateral MVN neurons dynamically responding to input stimuli is still largely unknown. In the present study, by using qPCR, whole-cell patch clamp recording in acute brain slices and behavioral techniques, we observed that 6 h after UL, rats showed a significant deficit in spontaneous locomotion, and a decrease in excitability of type B neurons in the ipsilesional rather than contralesional MVN. By contrast, type B neurons in the contralesional rather than ipsilesional MVN exhibited an increase in response sensitivity to the ramp and step input current stimuli. One week after UL, both the neuronal excitability of the ipsilesional MVN and the neuronal sensitivity of the contralesional MVN recovered to the baseline, accompanied by a compensation of spontaneous locomotion. In addition, the data showed that the small conductance Ca2+-activated K+ (SK) channel involved in the regulation of type B MVN neuronal sensitivity, showed a selective decrease in expression in the contralesional MVN 6 h after UL, and returned to normal level 1 week later. Pharmacological blockage of SK channel in contralateral MVN to inhibit the UL-induced functional plasticity of SK channel significantly delayed the compensation of vestibular motor dysfunction. These results suggest that the changes in plasticity of the ipsilesional MVN neuronal excitability, together with changes in the contralesional MVN neuronal sensitivity, may both contribute to the development of vestibular symptoms as well as vestibular compensation, and SK channel may be an essential ionic mechanism responsible for the dynamic changes of MVN neuronal sensitivity during vestibular compensation.

Metabolomic study for essential hypertension patients based on dried blood spot mass spectrometry approach.

Hypertension is an increasingly serious public-health challenge worldwide. The traditional blood pressure measurement method could easily and reliably detect blood pressure. However, the delayed symptom onset may influence the screening of essential hypertension (EH). In addition, EH is significantly associated to cardiovascular disease, stroke and kidney disease. Hence, it is urgent to define associated biomarkers with early diagnosis potential for EH. A dried blood spot method integrated with direct infusion mass spectrometry (MS) metabolomic analysis was applied for the detection of metabolites toward 87 EH patients and 91 healthy controls (HC). Multiple algorithms were run on training set (62 EH and 64 HC) for selecting differential metabolites as potential biomarkers. A test set (25 EH and 27 HC) was used to verify and evaluate selected potential biomarkers. A novel blood biomarker model based on Gly, Orn, C10, Orn/Cit, Phe/Tyr, and C5-OH/C8 exhibited potential to differentiate EH patients from HC individuals, with a sensitivity of 0.8400 and a specificity of 0.8889 in test set. The metabolomic analysis of EH is beneficial to the definition of disease-associated biomarkers and the development of new diagnostic approaches. © 2018 IUBMB Life, 70(8):777-785, 2018.

Study of the instability of the Poiseuille flow using a thermodynamic formalism.

The stability of the plane Poiseuille flow is analyzed using a thermodynamic formalism by considering the deterministic Navier-Stokes equation with Gaussian random initial data. A unique critical Reynolds number, Rec ≈ 2,332, at which the probability of observing puffs in the solution changes from 0 to 1, is numerically demonstrated to exist in the thermodynamic limit and is found to be independent of the noise amplitude. Using the puff density as the macrostate variable, the free energy of such a system is computed and analyzed. The puff density approaches zero as the critical Reynolds number is approached from above, signaling a continuous transition despite the fact that the bifurcation is subcritical for a finite-sized system. An action function is found for the probability of observing puffs in a small subregion of the flow, and this action function depends only on the Reynolds number. The strategy used here should be applicable to a wide range of other problems exhibiting subcritical instabilities.

Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator.

Numerical approximation methods for the Koopman operator have advanced considerably in the last few years. In particular, data-driven approaches such as dynamic mode decomposition (DMD)51 and its generalization, the extended-DMD (EDMD), are becoming increasingly popular in practical applications. The EDMD improves upon the classical DMD by the inclusion of a flexible choice of dictionary of observables which spans a finite dimensional subspace on which the Koopman operator can be approximated. This enhances the accuracy of the solution reconstruction and broadens the applicability of the Koopman formalism. Although the convergence of the EDMD has been established, applying the method in practice requires a careful choice of the observables to improve convergence with just a finite number of terms. This is especially difficult for high dimensional and highly nonlinear systems. In this paper, we employ ideas from machine learning to improve upon the EDMD method. We develop an iterative approximation algorithm which couples the EDMD with a trainable dictionary represented by an artificial neural network. Using the Duffing oscillator and the Kuramoto Sivashinsky partical differential equation as examples, we show that our algorithm can effectively and efficiently adapt the trainable dictionary to the problem at hand to achieve good reconstruction accuracy without the need to choose a fixed dictionary a priori. Furthermore, to obtain a given accuracy, we require fewer dictionary terms than EDMD with fixed dictionaries. This alleviates an important shortcoming of the EDMD algorithm and enhances the applicability of the Koopman framework to practical problems.

Beneficial effects of intramyocardial mesenchymal stem cells and VEGF165 plasmid injection in rats with furazolidone induced dilated cardiomyopathy.

To explore the impact of myocardial injection of mesenchymal stem cells (MSCs) and specific recombinant human VEGF165 (hVEGF165 ) plasmid on collagen remodelling in rats with furazolidone induced dilated cardiomyopathy (DCM). DCM was induced by furazolidone (0.3 mg/bodyweight (g)/day per gavage for 8 weeks). Rats were then divided into four groups: (i) PBS group (n = 18): rats received equal volume myocardial PBS injection; (ii) MSCs group (n = 17): 100 µl culture medium containing 10(5) MSCs were injected into four sites of left ventricular free wall (25 µl per site); (iii) GENE group (n = 18): pCMVen-MLC2v-EGFP-VEGF165 plasmid [5 × 10(9) pfu (0.2 ml)] were injected into four sites of left ventricular free wall (0.05 ml per site)] and (iv) MSCs+GENE group (n = 17): rats received both myocardial MSCs and pCMVen-MLC2v-EGFP-VEGF165 plasmid injections. After 4 weeks, cardiac function was evaluated by echocardiography. Myocardial mRNA expressions of type I, type III collagen and transforming growth factor (TGF)-ß1 were detected by RT-PCR. The protein expression of hVEGF165 was determined by Western blot. Myocardial protein expression of hVEGF165 was demonstrated in GENE and MSCs+GENE groups. Cardiac function was improved in MSCs, GENE and MSCs+GENE groups. Collagen volume fraction was significantly reduced and myocardial TGF-ß1 mRNA expression significantly down-regulated in both GENE and MSCs+GENE groups, collagen type I/III ratio reduction was more significant in MSCs+GENE group than in MSCs or GENE group. Myocardial MSCs and hVEGF165 plasmid injection improves cardiac function possibly through down-regulating myocardial TGF-ß1 expression and reducing the type I/III collagen ratio in this DCM rat model.

Impact of repeated intravenous bone marrow mesenchymal stem cells infusion on myocardial collagen network remodeling in a rat model of doxorubicin-induced dilated cardiomyopathy.

Bone marrow mesenchymal stem cells (MSCs) transplantation improved cardiac function and reduced myocardial fibrosis in both ischemic and non-ischemic cardiomyopathies. We evaluated the effects of repeated peripheral vein injection of MSCs on collagen network remodeling and myocardial TGF-ß1, AT1, CYP11B2 (aldosterone synthase) gene expressions in a rat model of doxorubicin (DOX)-induced dilated cardiomyopathy (DCM). Thirty-eight out of 53 SD rats survived at 10 weeks post-DOX injection (2.5 mg/kg/week for 6 weeks, i.p.) were divided into DCM blank (without treatment, n = 12), DCM placebo (intravenous tail injection of 0.5 mL serum-free culture medium every other day for ten times, n = 13), and DCM plus MSCs group (intravenous tail injection of 5 × 10(6) MSCs dissolved in 0.5 mL serum-free culture medium every other day for 10 times, n = 13). Ten untreated rats served as normal controls. At 20 weeks after DOX injection, echocardiography, myocardial collagen content, myocardial expressions of types I and III collagen, TGF-ß1, AT1, and CYP11B2 were compared among groups. At 20 weeks post-DOX injection, 8 rats (67%) survived in DCM blank group, 9 rats (69%) survived in DCM placebo group while 13 rats (100 %) survived in DCM plus MSCs group. Left ventricular end-diastolic diameter was significantly higher and ejection fraction was significantly lower in DCM blank and DCM placebo groups compared to normal control rats, which were significantly improved in DCM plus MSCs group (all p < 0.05 vs. DCM blank and DCM placebo groups). Moreover, myocardial collagen volume fraction, types I and III collagen, myocardial mRNA expressions of TGF-ß1, AT1, CYP11B2, and collagen I/III ratio were all significantly lower in DCM plus MSCs group compared to DCM blank and DCM placebo groups (all p < 0.05). Repeated intravenous MSCs transplantation could improve cardiac function by attenuating myocardial collagen network remodeling possibly through downregulating renin-angiotensin-aldosterone system in DOX-induced DCM rats.

Constructing custom thermodynamics using deep learning.

One of the most exciting applications of artificial intelligence is automated scientific discovery based on previously amassed data, coupled with restrictions provided by known physical principles, including symmetries and conservation laws. Such automated hypothesis creation and verification can assist scientists in studying complex phenomena, where traditional physical intuition may fail. Here we develop a platform based on a generalized Onsager principle to learn macroscopic dynamical descriptions of arbitrary stochastic dissipative systems directly from observations of their microscopic trajectories. Our method simultaneously constructs reduced thermodynamic coordinates and interprets the dynamics on these coordinates. We demonstrate its effectiveness by studying theoretically and validating experimentally the stretching of long polymer chains in an externally applied field. Specifically, we learn three interpretable thermodynamic coordinates and build a dynamical landscape of polymer stretching, including the identification of stable and transition states and the control of the stretching rate. Our general methodology can be used to address a wide range of scientific and technological applications.

An Annealing Mechanism for Adversarial Training Acceleration.

Despite the empirical success in various domains, it has been revealed that deep neural networks are vulnerable to maliciously perturbed input data that can dramatically degrade their performance. These are known as adversarial attacks. To counter adversarial attacks, adversarial training formulated as a form of robust optimization has been demonstrated to be effective. However, conducting adversarial training brings much computational overhead compared with standard training. In order to reduce the computational cost, we propose an annealing mechanism, annealing mechanism for adversarial training acceleration (Amata), to reduce the overhead associated with adversarial training. The proposed Amata is provably convergent, well-motivated from the lens of optimal control theory, and can be combined with existing acceleration methods to further enhance performance. It is demonstrated that, on standard datasets, Amata can achieve similar or better robustness with around 1/3-1/2 the computational time compared with traditional methods. In addition, Amata can be incorporated into other adversarial training acceleration algorithms (e.g., YOPO, Free, Fast, and ATTA), which leads to a further reduction in computational time on large-scale problems.

Dynamic Modeling of Intrinsic Self-Healing Polymers Using Deep Learning.

The properties of self-healing polymers are traditionally identified through destructive testing. This means that the mechanics are explored in hindsight with either theoretical derivations and/or simulations. Here, a self-healing property evolution using energy functional dynamical (SPEED) model is proposed to predict and understand the mechanics of self-healing of polymers using images of cuts dynamically healing over time. Using machine learning, an energy functional minimization (EFM) model extracted an effective underlying dynamical system from a time series of two-dimensional cut images on a self-healing polymer of constant thickness. This model can be used to capture the physics behind the self-healing dynamics in terms of potential and interface energies. When combined with a static property prediction model, the SPEED model can predict the macroscopic evolution of material properties after training only on a small set of experimental measurements. Such temporal evolutions are usually inaccessible from pure experiments or computational modeling due to the need for destructive testing. As an example, we validate this approach on toughness measurements of an intrinsic self-healing conductive polymer by capturing over 100 000 image frames of cuts to build the machine learning (ML) model. The results show that the SPEED model can be applied to predict the temporal evolution of macroscopic properties using few measurements as training data.

A comparative study of vestibular improvement and gastrointestinal effect of betahistine and gastrodin in mice.

Betahistine and gastrodin are the first-line medications for vestibular disorders in clinical practice, nevertheless, their amelioration effects on vestibular dysfunctions still lack direct comparison and their unexpected extra-vestibular effects remain elusive. Recent clinical studies have indicated that both of them may have effects on the gastrointestinal (GI) tract. Therefore, we purposed to systematically compare both vestibular and GI effects induced by betahistine and gastrodin and tried to elucidate the mechanisms underlying their GI effects. Our results showed that betahistine and gastrodin indeed had similar therapeutic effects on vestibular-associated motor dysfunction induced by unilateral labyrinthectomy. However, betahistine reduced total GI motility with gastric hypomotility and colonic hypermotility, whereas gastrodin did not influence total GI motility with only slight colonic hypermotility. In addition, betahistine, at normal dosages, induced a slight injury of gastric mucosa. These GI effects may be due to the different effects of betahistine and gastrodin on substance P and vasoactive intestinal peptide secretion in stomach and/or colon, and agonistic/anatgonistic effects of betahistine on histamine H1 and H3 receptors expressed in GI mucosal cells and H3 receptors distributed on nerves within the myenteric and submucosal plexuses. Furthermore, treatment of betahistine and gastrodin had potential effects on gut microbiota composition, which could lead to changes in host-microbiota homeostasis in turn. These results demonstrate that gastrodin has a consistent improvement effect on vestibular functions compared with betahistine but less effect on GI functions and gut microbiota, suggesting that gastrodin may be more suitable for vestibular disease patients with GI dysfunction.

A Comparison on Prevalence of Hypertension and Related Risk Factors between Island and Rural Residents of Dalian City, China.

This study aimed to compare the prevalence of hypertension between the island and rural residents in Dalian, China, and to explore associated risk factors of hypertension in order to provide evidence for the establishment of targeted strategy of hypertension prevention and treatment for island and rural residents. The modified MONICA questionnaire survey was performed on 7764 island and rural residents aged ≥40 years (including 2652 island residents and 5112 rural residents). Our data showed that totally weighted prevalence of hypertension was significantly higher in rural residents than in island residents (61.9% vs. 55.2%, P<0.001). Multivariate binary logistic regression analysis showed that older age, higher BMI, lower education level, and higher LDL-C and UA levels were independently associated with increased risk of having hypertension both in island and in rural residents. The weighted awareness rate (29.9% vs. 17.3%, P<0.001), treatment rate (51.4% vs. 28.5%, P<0.001), and control rate (36.3% vs. 24.0%, P=0.001) of hypertension were all significantly higher in island residents than those in rural residents. In conclusion, our survey shows that the epidemics of hypertension are extremely high in surveyed residents in island and rural areas of Dalian city, while awareness, treatment, and control rats of hypertension in these residents are much lower than the national level. The scenario is even worse in rural residents as compared with island residents of Dalian, China.

An Emergent Space for Distributed Data with Hidden Internal Order through Manifold Learning.

Manifold-learning techniques are routinely used in mining complex spatiotemporal data to extract useful, parsimonious data representations/parametrizations; these are, in turn, useful in nonlinear model identification tasks. We focus here on the case of time series data that can ultimately be modelled as a spatially distributed system (e.g. a partial differential equation, PDE), but where we do not know the space in which this PDE should be formulated. Hence, even the spatial coordinates for the distributed system themselves need to be identified - to "emerge from"-the data mining process. We will first validate this "emergent space" reconstruction for time series sampled without space labels in known PDEs; this brings up the issue of observability of physical space from temporal observation data, and the transition from spatially resolved to lumped (order-parameter-based) representations by tuning the scale of the data mining kernels. We will then present actual emergent space "discovery" illustrations. Our illustrative examples include chimera states (states of coexisting coherent and incoherent dynamics), and chaotic as well as quasiperiodic spatiotemporal dynamics, arising in partial differential equations and/or in heterogeneous networks. We also discuss how data-driven "spatial" coordinates can be extracted in ways invariant to the nature of the measuring instrument. Such gauge-invariant data mining can go beyond the fusion of heterogeneous observations of the same system, to the possible matching of apparently different systems. For an older version of this article, including other examples, see https://arxiv.org/abs/1708.05406.

Omega-3 polyunsaturated fatty acids prevent murine dilated cardiomyopathy by reducing oxidative stress and cardiomyocyte apoptosis.

Mice that lacked manganese-superoxide dismutase (Mn-SOD) activity exhibited the typical pathology of dilated cardiomyopathy (DCM). The aim of the present study was to investigate the effect of supplementation with omega-3 polyunsaturated fatty acids (n-3 PUFA) on heart function and oxidative stress biomarkers in mice with DCM. In the present study, heart/muscle-specific Mn-SOD-deficient mice (H/M-Sod2-/-) were treated with n-3 PUFA (30 mg/kg/day) for 10 weeks, and the reactive oxygen species (ROS) production in their heart mitochondria and cardiac function was subsequently assessed. n-3 PUFA treatment diminished ROS production and suppressed the progression of cardiac dysfunction. Furthermore, n-3 PUFA treatment effectively reversed the cardiac dysfunction and dilatation observed in symptomatic H/M-Sod2-/- mice. Notably, n-3 PUFA treatment ameliorated a molecular defect in connexin 43. Hematoxylin-eosin staining indicated that the phenotype of DCM was also ameliorated following n-3 PUFA treatment. Furthermore, echocardiography demonstrated that cardiac function was significantly improved in the mice treated with n-3 PUFA (P<0.05). Meanwhile, pre-treatment with n-3 PUFA significantly decreased cardiomyocyte apoptosis (P<0.001). In conclusion, n-3 PUFA treatment is able to prevent murine DCM, primarily by reducing ROS production and improving myocardial apoptosis. Therefore, the impairment of ROS production is proposed as a potential therapy for DCM.