Effect of ozone gas on viral kinetics and liver histopathology in hepatitis C patients.

OBJECTIVES: We examine how well ozone/oxygen gas therapy treats chronic hepatitis C patients with varying degrees of liver fibrosis. Also to study the effect of giving multiple anti-oxidants with the ozone/oxygen gas mixture, to see if this addition would have any additive or synergistic effect. METHODS: Two hundred and twenty three patients with chronic hepatitis C. Liver biopsies were carried out at after 12 weeks of administering an ozone/oxygen gas mixture. RESULTS: The mean stage of fibrosis decreased from 1.98 to 1.41 and the mean grade of inflammation decreased from 10.08 to 7.94, both with a p value less than 0.001. After 12 weeks of treatment, mean PCR values increased. No single significant complication was recorded in a total of >9,000 settings of ozone therapy. CONCLUSIONS: Ozone oxygen gas mixture is safe and effective in treatment of hepatic fibrosis due to chronic viral hepatitis C.

Chronic brain functional ultrasound imaging in freely moving rodents performing cognitive tasks.

BACKGROUND: Functional ultrasound imaging (fUS) is an emerging imaging technique that indirectly measures neural activity via changes in blood volume. Chronic fUS imaging during cognitive tasks in freely moving animals faces multiple exceptional challenges: performing large durable craniotomies with chronic implants, designing behavioral experiments matching the hemodynamic timescale, stabilizing the ultrasound probe during freely moving behavior, accurately assessing motion artifacts, and validating that the animal can perform cognitive tasks while tethered. NEW METHOD: We provide validated solutions for those technical challenges. In addition, we present standardized step-by-step reproducible protocols, procedures, and data processing pipelines. Finally, we present proof-of-concept analysis of brain dynamics during a decision making task. RESULTS: We obtain stable recordings from which we can robustly decode task variables from fUS data over multiple months. Moreover, we find that brain wide imaging through hemodynamic response is nonlinearly related to cognitive variables, such as task difficulty, as compared to sensory responses previously explored. COMPARISON WITH EXISTING METHODS: Computational pipelines in fUS are nascent and we present an initial development of a full processing pathway to correct and segment fUS data. CONCLUSIONS: Our methods provide stable imaging and analysis of behavior with fUS that will enable new experimental paradigms in understanding brain-wide dynamics in naturalistic behaviors.

Everyone knows what behavior is but they just don't agree on it.

Studying "behavior" lies at the heart of many disciplines. Nevertheless, academics rarely provide an explicit definition of what "behavior" actually is. What range of definitions do people use, and how does that vary across disciplines? To answer these questions, we have developed a survey to probe what constitutes "behavior." We find that academics adopt different definitions of behavior according to their academic discipline, animal model that they work with, and level of academic seniority. Using hierarchical clustering, we identify at least six distinct types of "behavior" which are used in seven distinct operational archetypes of "behavior." Individual respondents have clear consistent definitions of behavior, but these definitions are not consistent across the population. Our study is a call for academics to clarify what they mean by "behavior" wherever they study it, with the hope that this will foster interdisciplinary studies that will improve our understanding of behavioral phenomena.

Melatonin-vorinostat hybrid ligands show higher histone deacetylase and cancer cell growth inhibition than vorinostat.

Anticancer drug conjugates are an emerging approach for future cancer treatment. Here, we report a series of hybrid ligands merging the neurohormone melatonin with the approved histone deacetylase (HDAC) inhibitor vorinostat, using melatonin's amide side chain (3a-e), its indolic nitrogen (5a-d), and its ether oxygen (7a-d) as attachment points. Several hybrid ligands showed higher potency thanvorinostat in both HDAC inhibition and cellular assays on different cultured cancer cell lines. In the most potent HDAC1 and HDAC6 inhibitors, 3e, 5c, and 7c, the hydroxamic acid moiety of vorinostat is linked to melatonin through a hexamethylene spacer. Hybrid ligands 5c and 7c were also found to be potent growth inhibitors of MCF-7, PC-3M-Luc, and HL-60 cancer cell lines. As these compounds showed only weak agonist activity at melatonin MT1 receptors, the findings indicate that their anticancer actions are driven by HDAC inhibition.

Stochastic dynamics of social patch foraging decisions.

Animals typically forage in groups. Social foraging can help animals avoid predation and decrease their uncertainty about the richness of food resources. Despite this, theoretical mechanistic models of patch foraging have overwhelmingly focused on the behavior of single foragers. In this study, we develop a mechanistic model that accounts for the behavior of individuals foraging together and departing food patches following an evidence accumulation process. Each individual's belief about patch quality is represented by a stochastically accumulating variable, which is coupled to another's belief to represent the transfer of information. We consider a cohesive group, and model information sharing by considering both intermittent pulsatile coupling (only communicate decision to leave) and continuous diffusive coupling (communicate throughout the deliberation process). Groups employing pulsatile coupling can obtain higher foraging efficiency, which depends more strongly on the coupling parameter compared to those using diffusive coupling. Conversely, groups using diffusive coupling are more robust to changes and heterogeneities in belief weighting and departure criteria. Efficiency is measured by a reward rate function that balances the amount of energy accumulated against the time spent in a patch, computed by solving an ordered first passage time problem for the patch departures of each individual. Using synthetic departure time data, we can distinguish between the two modes of communication and identify the model parameters. Our model establishes a social patch foraging framework to identify deliberative decision strategies and forms of social communication, and to allow model fitting to field data from foraging animal groups.

Active neural coordination of motor behaviors with internal states.

The brain continuously coordinates skeletomuscular movements with internal physiological states like arousal, but how is this coordination achieved? One possibility is that the brain simply reacts to changes in external and/or internal signals. Another possibility is that it is actively coordinating both external and internal activities. We used functional ultrasound imaging to capture a large medial section of the brain, including multiple cortical and subcortical areas, in marmoset monkeys while monitoring their spontaneous movements and cardiac activity. By analyzing the causal ordering of these different time series, we found that information flowing from the brain to movements and heart-rate fluctuations were significantly greater than in the opposite direction. The brain areas involved in this external versus internal coordination were spatially distinct, but also extensively interconnected. Temporally, the brain alternated between network states for this regulation. These findings suggest that the brain's dynamics actively and efficiently coordinate motor behavior with internal physiology.

Stable choice coding in rat frontal orienting fields across model-predicted changes of mind.

During decision making in a changing environment, evidence that may guide the decision accumulates until the point of action. In the rat, provisional choice is thought to be represented in frontal orienting fields (FOF), but this has only been tested in static environments where provisional and final decisions are not easily dissociated. Here, we characterize the representation of accumulated evidence in the FOF of rats performing a recently developed dynamic evidence accumulation task, which induces changes in the provisional decision, referred to as "changes of mind". We find that FOF encodes evidence throughout decision formation with a temporal gain modulation that rises until the period when the animal may need to act. Furthermore, reversals in FOF firing rates can be accounted for by changes of mind predicted using a model of the decision process fit only to behavioral data. Our results suggest that the FOF represents provisional decisions even in dynamic, uncertain environments, allowing for rapid motor execution when it is time to act.

Uncertainty drives deviations in normative foraging decision strategies.

Nearly all animals forage to acquire energy for survival through efficient search and resource harvesting. Patch exploitation is a canonical foraging behaviour, but there is a need for more tractable and understandable mathematical models describing how foragers deal with uncertainty. To provide such a treatment, we develop a normative theory of patch foraging decisions, proposing mechanisms by which foraging behaviours emerge in the face of uncertainty. Our model foragers statistically and sequentially infer patch resource yields using Bayesian updating based on their resource encounter history. A decision to leave a patch is triggered when the certainty of the patch type or the estimated yield of the patch falls below a threshold. The time scale over which uncertainty in resource availability persists strongly impacts behavioural variables like patch residence times and decision rules determining patch departures. When patch depletion is slow, as in habitat selection, departures are characterized by a reduction of uncertainty, suggesting that the forager resides in a low-yielding patch. Uncertainty leads patch-exploiting foragers to overharvest (underharvest) patches with initially low (high) resource yields in comparison with predictions of the marginal value theorem. These results extend optimal foraging theory and motivate a variety of behavioural experiments investigating patch foraging behaviour.

Systems Neuroscience of Natural Behaviors in Rodents.

Animals evolved in complex environments, producing a wide range of behaviors, including navigation, foraging, prey capture, and conspecific interactions, which vary over timescales ranging from milliseconds to days. Historically, these behaviors have been the focus of study for ecology and ethology, while systems neuroscience has largely focused on short timescale behaviors that can be repeated thousands of times and occur in highly artificial environments. Thanks to recent advances in machine learning, miniaturization, and computation, it is newly possible to study freely moving animals in more natural conditions while applying systems techniques: performing temporally specific perturbations, modeling behavioral strategies, and recording from large numbers of neurons while animals are freely moving. The authors of this review are a group of scientists with deep appreciation for the common aims of systems neuroscience, ecology, and ethology. We believe it is an extremely exciting time to be a neuroscientist, as we have an opportunity to grow as a field, to embrace interdisciplinary, open, collaborative research to provide new insights and allow researchers to link knowledge across disciplines, species, and scales. Here we discuss the origins of ethology, ecology, and systems neuroscience in the context of our own work and highlight how combining approaches across these fields has provided fresh insights into our research. We hope this review facilitates some of these interactions and alliances and helps us all do even better science, together.

WITHDRAWN:Evaluation of lipid profile, antioxidant and immunity statuses of rabbits fed Moringa oleifera leaves.

Ahead of Print article withdrawn by publisher.

Productive performance, lipid profile and caecum microbial counts of growing rabbits treated with humic acid.

The aim of the present study was to evaluate the effect of a humic acid (HA)-supplemented diet on productive performance and some physiological parameters of growing rabbits. A total of 80 weaned V-line rabbits at an age of 4 weeks were randomly divided into four groups. Rabbits of groups 2, 3 and 4 were fed diet containing 35 (HA35), 70 (HA70) and 105 (HA105) mg Humic acid/kg diet while the first group served as control (HA0). Body weight gain was positively affected by HA treatment. HA105 rabbits had the improved feed conversion value. HA treatments had significantly reduced plasma cholesterol concentration and significant increased red blood cells, white blood cells count and plasma high-density lipoprotein concentrations. However, serum aspartate amino transferase and alanine amino transferase activities, creatinine and the apparent nutrients digestibility values were not affected by HA treatments. Organic matter digestibility of all HA-treated groups significantly increased compared with HA0. At 63 days of age (after 35 days of treatment), caecum microbial counts decreased (total bacteria and Escherichia coli) with HA treatments. Generally HA could be considered as a biological as growth promoter feed additive alternative to antibiotics.

Axonal Computations.

Axons functionally link the somato-dendritic compartment to synaptic terminals. Structurally and functionally diverse, they accomplish a central role in determining the delays and reliability with which neuronal ensembles communicate. By combining their active and passive biophysical properties, they ensure a plethora of physiological computations. In this review, we revisit the biophysics of generation and propagation of electrical signals in the axon and their dynamics. We further place the computational abilities of axons in the context of intracellular and intercellular coupling. We discuss how, by means of sophisticated biophysical mechanisms, axons expand the repertoire of axonal computation, and thereby, of neural computation.

Foraging as an evidence accumulation process.

The patch-leaving problem is a canonical foraging task, in which a forager must decide to leave a current resource in search for another. Theoretical work has derived optimal strategies for when to leave a patch, and experiments have tested for conditions where animals do or do not follow an optimal strategy. Nevertheless, models of patch-leaving decisions do not consider the imperfect and noisy sampling process through which an animal gathers information, and how this process is constrained by neurobiological mechanisms. In this theoretical study, we formulate an evidence accumulation model of patch-leaving decisions where the animal averages over noisy measurements to estimate the state of the current patch and the overall environment. We solve the model for conditions where foraging decisions are optimal and equivalent to the marginal value theorem, and perform simulations to analyze deviations from optimal when these conditions are not met. By adjusting the drift rate and decision threshold, the model can represent different "strategies", for example an incremental, decremental, or counting strategy. These strategies yield identical decisions in the limiting case but differ in how patch residence times adapt when the foraging environment is uncertain. To describe sub-optimal decisions, we introduce an energy-dependent marginal utility function that predicts longer than optimal patch residence times when food is plentiful. Our model provides a quantitative connection between ecological models of foraging behavior and evidence accumulation models of decision making. Moreover, it provides a theoretical framework for potential experiments which seek to identify neural circuits underlying patch-leaving decisions.

Rats adopt the optimal timescale for evidence integration in a dynamic environment.

Decision making in dynamic environments requires discounting old evidence that may no longer inform the current state of the world. Previous work found that humans discount old evidence in a dynamic environment, but do not discount at the optimal rate. Here we investigated whether rats can optimally discount evidence in a dynamic environment by adapting the timescale over which they accumulate evidence. Using discrete evidence pulses, we exactly compute the optimal inference process. We show that the optimal timescale for evidence discounting depends on both the stimulus statistics and noise in sensory processing. When both of these components are taken into account, rats accumulate and discount evidence with the optimal timescale. Finally, by changing the volatility of the environment, we demonstrate experimental control over the rats' accumulation timescale. The mechanisms supporting integration are a subject of extensive study, and experimental control over these timescales may open new avenues of investigation.

SK3 Channel Overexpression in Mice Causes Hippocampal Shrinkage Associated with Cognitive Impairments.

The dysfunction of the small-conductance calcium-activated K+ channel SK3 has been described as one of the factors responsible for the progress of psychoneurological diseases, but the molecular basis of this is largely unknown. This report reveals through use of immunohistochemistry and computational tomography that long-term increased expression of the SK3 small-conductance calcium-activated potassium channel (SK3-T/T) in mice induces a notable bilateral reduction of the hippocampal area (more than 50 %). Histological analysis showed that SK3-T/T mice have cellular disarrangements and neuron discontinuities in the hippocampal formation CA1 and CA3 neuronal layer. SK3 overexpression resulted in cognitive loss as determined by the object recognition test. Electrophysiological examination of hippocampal slices revealed that SK3 channel overexpression induced deficiency of long-term potentiation in hippocampal microcircuits. In association with these results, there were changes at the mRNA levels of some genes involved in Alzheimer's disease and/or linked to schizophrenia, epilepsy, and autism. Taken together, these features suggest that augmenting the function of SK3 ion channel in mice may present a unique opportunity to investigate the neural basis of central nervous system dysfunctions associated with schizophrenia, Alzheimer's disease, or other neuropsychiatric/neurodegenerative disorders in this model system. As a more detailed understanding of the role of the SK3 channel in brain disorders is limited by the lack of specific SK3 antagonists and agonists, the results observed in this study are of significant interest; they suggest a new approach for the development of neuroprotective strategies in neuropsychiatric/neurodegenerative diseases with SK3 representing a potential drug target.

Growing neuronal islands on multi-electrode arrays using an accurate positioning-µCP device.

BACKGROUND: Multi-electrode arrays (MEAs) allow non-invasive multi-unit recording in-vitro from cultured neuronal networks. For sufficient neuronal growth and adhesion on such MEAs, substrate preparation is required. Plating of dissociated neurons on a uniformly prepared MEA's surface results in the formation of spatially extended random networks with substantial inter-sample variability. Such cultures are not optimally suited to study the relationship between defined structure and dynamics in neuronal networks. To overcome these shortcomings, neurons can be cultured with pre-defined topology by spatially structured surface modification. Spatially structuring a MEA surface accurately and reproducibly with the equipment of a typical cell-culture laboratory is challenging. NEW METHOD: In this paper, we present a novel approach utilizing micro-contact printing (µCP) combined with a custom-made device to accurately position patterns on MEAs with high precision. We call this technique AP-µCP (accurate positioning micro-contact printing). COMPARISON WITH EXISTING METHODS: Other approaches presented in the literature using µCP for patterning either relied on facilities or techniques not readily available in a standard cell culture laboratory, or they did not specify means of precise pattern positioning. CONCLUSION: Here we present a relatively simple device for reproducible and precise patterning in a standard cell-culture laboratory setting. The patterned neuronal islands on MEAs provide a basis for high throughput electrophysiology to study the dynamics of single neurons and neuronal networks.

Mechanical surface waves accompany action potential propagation.

Many diverse studies have shown that a mechanical displacement of the axonal membrane accompanies the electrical pulse defining the action potential (AP). We present a model for these mechanical displacements as arising from the driving of surface wave modes in which potential energy is stored in elastic properties of the neuronal membrane and cytoskeleton while kinetic energy is carried by the axoplasmic fluid. In our model, these surface waves are driven by the travelling wave of electrical depolarization characterizing the AP, altering compressive electrostatic forces across the membrane. This driving leads to co-propagating mechanical displacements, which we term Action Waves (AWs). Our model allows us to estimate the shape of the AW that accompanies any travelling wave of voltage, making predictions that are in agreement with results from several experimental systems. Our model can serve as a framework for understanding the physical origins and possible functional roles of these AWs.

STED nanoscopy reveals the ubiquity of subcortical cytoskeleton periodicity in living neurons.

In the axons of cultured hippocampal neurons, actin forms various structures, including bundles, patches (involved in the preservation of neuronal polarity), and a recently reported periodic ring-like structure. Nevertheless, the overlaying organization of actin in neurons and in the axon initial segment (AIS) is still unclear, due mainly to a lack of adequate imaging methods. By harnessing live-cell stimulated emission depletion (STED) nanoscopy and the fluorescent probe SiR-Actin, we show that the periodic subcortical actin structure is in fact present in both axons and dendrites. The periodic cytoskeleton organization is also found in the peripheral nervous system, specifically at the nodes of Ranvier. The actin patches in the AIS co-localize with pre-synaptic markers. Cytosolic actin organization strongly depends on the developmental stage and subcellular localization. Altogether, the results of this study reveal unique neuronal cytoskeletal features.

Optogenetic stimulation effectively enhances intrinsically generated network synchrony.

Synchronized bursting is found in many brain areas and has also been implicated in the pathophysiology of neuropsychiatric disorders such as epilepsy, Parkinson's disease, and schizophrenia. Despite extensive studies of network burst synchronization, it is insufficiently understood how this type of network wide synchronization can be strengthened, reduced, or even abolished. We combined electrical recording using multi-electrode array with optical stimulation of cultured channelrhodopsin-2 transducted hippocampal neurons to study and manipulate network burst synchronization. We found low frequency photo-stimulation protocols that are sufficient to induce potentiation of network bursting, modifying bursting dynamics, and increasing interneuronal synchronization. Surprisingly, slowly fading-in light stimulation, which substantially delayed and reduced light-driven spiking, was at least as effective in reorganizing network dynamics as much stronger pulsed light stimulation. Our study shows that mild stimulation protocols that do not enforce particular activity patterns onto the network can be highly effective inducers of network-level plasticity.